{"jobs":[{"id":"11208bdc-a679-4cf7-b7a9-67848f7660ab","title":"Robotics Service Technician","department":"Hardware","team":"Hardware","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2025-07-30T00:43:15.130+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/11208bdc-a679-4cf7-b7a9-67848f7660ab","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/11208bdc-a679-4cf7-b7a9-67848f7660ab/application","descriptionHtml":"<p style=\"min-height:1.5em\">As a Robotics Service Technician at Physical Intelligence, you will play a critical role in maintaining our fleet of advanced robotic systems. You will be responsible for the electrical and mechanical upkeep of robotic platforms, ensuring they are running at peak performance and minimizing downtime. This role requires skills in both mechanical systems and electrical components, including troubleshooting, diagnostics, and hands-on repairs.</p><p style=\"min-height:1.5em\">The ideal candidate will have a blend of hands-on mechanical and electrical system repair expertise, be highly detail-oriented, and the ability to work in a dynamic, high-tech environment.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"As a Robotics Service Technician at Physical Intelligence, you will play a critical role in maintaining our fleet of advanced robotic systems. You will be responsible for the electrical and mechanical upkeep of robotic platforms, ensuring they are running at peak performance and minimizing downtime. This role requires skills in both mechanical systems and electrical components, including troubleshooting, diagnostics, and hands-on repairs.\n\nThe ideal candidate will have a blend of hands-on mechanical and electrical system repair expertise, be highly detail-oriented, and the ability to work in a dynamic, high-tech environment.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"eb3ed968-630f-429a-9e44-5508b77d554b","title":"Robot Operator","department":"Operations","team":"Operations","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-02-11T00:51:52.982+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/eb3ed968-630f-429a-9e44-5508b77d554b","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/eb3ed968-630f-429a-9e44-5508b77d554b/application","descriptionHtml":"<h2><strong>About Physical Intelligence</strong></h2><p style=\"min-height:1.5em\">Physical Intelligence is building the future where AI-powered robots seamlessly integrate into our daily lives. Imagine a robot that can fold your laundry, prepare meals, and organize your space. Picture robots in warehouses that can handle any package, or manufacturing robots that can adapt to new products without reprogramming. We're making this vision reality by developing general-purpose AI that can control robots to perform any physical task.</p><p style=\"min-height:1.5em\">Our team of engineers, scientists, and roboticists is creating foundation models—the same breakthrough technology behind ChatGPT—but for the physical world. Just as language models learned to understand and generate text from massive datasets, our robots learn to interact with the physical world through high-quality demonstration data.<br /></p><h2><strong>The Role</strong></h2><p style=\"min-height:1.5em\">Data collection is the fuel that drives our mission. Every robot movement, every successful task completion, every demonstration you provide teaches our AI systems how to interact with the physical world. As a Robot Operator, you're not just controlling robots—you're literally training the AI that will power the next generation of intelligent machines.</p><p style=\"min-height:1.5em\">You'll be at the forefront of robotics AI, working hands-on with cutting-edge robotic systems to generate the high-quality training data our models need. Your precise demonstrations teach our AI everything from delicate manipulation tasks to complex multi-step processes. This is your chance to directly contribute to technology that will transform how robots help humans in homes, workplaces, and beyond.<br /></p><h2><strong>What You'll Do</strong></h2><p style=\"min-height:1.5em\"><strong>Primary Responsibilities</strong></p><p style=\"min-height:1.5em\">- Teleoperate robotic arms through a variety of tasks using our intuitive control systems</p><p style=\"min-height:1.5em\">- Either lead robot movements with your arms (the robot mirrors your actions) or guide robots using specialized controllers</p><p style=\"min-height:1.5em\">- Complete diverse tasks ranging from household activities like folding laundry to complex assembly work</p><p style=\"min-height:1.5em\">- Maintain high standards for data quality and consistency across all demonstrations</p><p style=\"min-height:1.5em\">- Meet established metrics for data collection volume and quality during your shift</p><p style=\"min-height:1.5em\"><strong>Important Note:</strong> This is a metrics-based role where you'll be expected to meet specific data collection goals throughout your shift. The work involves repetitive task execution, and the quality of data collection is extremely important to our AI training success. Watch some examples of training here:<a target=\"_blank\" rel=\"noopener noreferrer nofollow\" href=\"https://drive.google.com/drive/u/0/folders/1YPNYJxKF4i2U41o9pi5AzHCQFYaf2dnw\"> <u>https://drive.google.com/drive/u/0/folders/1YPNYJxKF4i2U41o9pi5AzHCQFYaf2dnw</u></a></p><p style=\"min-height:1.5em\"><strong>Example Tasks You'll Train Robots On</strong></p><p style=\"min-height:1.5em\">- Picking up grocery items and placing them in shipping bags</p><p style=\"min-height:1.5em\">- Sorting cups, plates, and utensils into bins</p><p style=\"min-height:1.5em\">- Opening and closing jars of various sizes</p><p style=\"min-height:1.5em\">- Folding different types of clothing and fabrics</p><p style=\"min-height:1.5em\">- Installing light bulbs and other simple assembly tasks</p><p style=\"min-height:1.5em\">- Multi-step electronics assembly processes</p><p style=\"min-height:1.5em\"><strong>Additional Duties</strong></p><p style=\"min-height:1.5em\">- Review and annotate videos of robot task performances using computer interfaces</p><p style=\"min-height:1.5em\">- Provide detailed feedback on robot performance and data quality</p><p style=\"min-height:1.5em\">- Assist with equipment setup and basic office tasks as needed</p><p style=\"min-height:1.5em\">- Participate in process improvements to enhance data collection efficiency</p><p style=\"min-height:1.5em\"><strong>Physical Requirements</strong></p><p style=\"min-height:1.5em\">- Ability to stand at a workstation for 8-hour shifts</p><p style=\"min-height:1.5em\">- Full use of both arms and hands for robot control</p><p style=\"min-height:1.5em\">- Good hand-eye coordination and manual dexterity</p><p style=\"min-height:1.5em\">- Attention to detail for quality control</p><h2><br /><strong>Work Environment &amp; Schedule</strong></h2><p style=\"min-height:1.5em\"><strong>Shift Options</strong> (8 hours with 30-minute lunch + two paid breaks):</p><p style=\"min-height:1.5em\"><strong>- Morning:</strong> 8:00 AM - 4:00 PM PT</p><p style=\"min-height:1.5em\"><strong>- Evening:</strong> 4:00 PM - 12:00 AM PT</p><p style=\"min-height:1.5em\"><strong>- Overnight:</strong> 12:00 AM -8:00 AM PT<br /></p><p style=\"min-height:1.5em\"><strong>Shift patterns:</strong> Mon-Fri, Wed-Sun, Sat-Wed</p><p style=\"min-height:1.5em\"><strong>Commitment:</strong> Minimum 5 days per week</p><p style=\"min-height:1.5em\"><strong>Compensation:</strong> $25/hour + benefits package<br /></p><h2><br /><strong>What We're Looking For</strong></h2><p style=\"min-height:1.5em\"><strong>Ideal Background</strong></p><p style=\"min-height:1.5em\">-  Experience with hands-on technical work, lab environments, or precision tasks</p><p style=\"min-height:1.5em\">- Interest in AI, robotics, and cutting-edge technology</p><p style=\"min-height:1.5em\">- Strong attention to detail and quality focus</p><p style=\"min-height:1.5em\"><strong>Key Qualities</strong></p><p style=\"min-height:1.5em\">- Meticulous attention to detail—data quality is crucial for AI training</p><p style=\"min-height:1.5em\">- Good manual dexterity and hand-eye coordination</p><p style=\"min-height:1.5em\">- Enjoys repetitive, precision-focused work</p><p style=\"min-height:1.5em\">- Thrives in fast-paced, metrics-driven environments</p><p style=\"min-height:1.5em\">- Excited about contributing to breakthrough AI research</p><p style=\"min-height:1.5em\">- Collaborative mindset and strong work ethic</p><p style=\"min-height:1.5em\"><strong>Nice to Have</strong></p><p style=\"min-height:1.5em\">- Experience with robotics systems or automation</p><p style=\"min-height:1.5em\">- Background in manufacturing, assembly, or laboratory work</p><p style=\"min-height:1.5em\">- Familiarity with AI/ML concepts</p><p style=\"min-height:1.5em\">- Gaming or simulation experience with controllers</p><h2><br /><strong>Why This Role Matters</strong></h2><p style=\"min-height:1.5em\">You'll be part of the team building the foundation for general-purpose robotics AI. Every demonstration you provide directly impacts our ability to create robots that can help with household chores, assist in workplaces, and improve quality of life. This is a rare opportunity to work at the cutting edge of AI and robotics while developing valuable technical skills in a rapidly growing field.</p><p style=\"min-height:1.5em\">Ready to help train the robots of tomorrow? We'd love to connect with you!</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"ABOUT PHYSICAL INTELLIGENCE\n\nPhysical Intelligence is building the future where AI-powered robots seamlessly integrate into our daily lives. Imagine a robot that can fold your laundry, prepare meals, and organize your space. Picture robots in warehouses that can handle any package, or manufacturing robots that can adapt to new products without reprogramming. We're making this vision reality by developing general-purpose AI that can control robots to perform any physical task.\n\nOur team of engineers, scientists, and roboticists is creating foundation models—the same breakthrough technology behind ChatGPT—but for the physical world. Just as language models learned to understand and generate text from massive datasets, our robots learn to interact with the physical world through high-quality demonstration data.\n\n\n\nTHE ROLE\n\nData collection is the fuel that drives our mission. Every robot movement, every successful task completion, every demonstration you provide teaches our AI systems how to interact with the physical world. As a Robot Operator, you're not just controlling robots—you're literally training the AI that will power the next generation of intelligent machines.\n\nYou'll be at the forefront of robotics AI, working hands-on with cutting-edge robotic systems to generate the high-quality training data our models need. Your precise demonstrations teach our AI everything from delicate manipulation tasks to complex multi-step processes. This is your chance to directly contribute to technology that will transform how robots help humans in homes, workplaces, and beyond.\n\n\n\nWHAT YOU'LL DO\n\nPrimary Responsibilities\n\n- Teleoperate robotic arms through a variety of tasks using our intuitive control systems\n\n- Either lead robot movements with your arms (the robot mirrors your actions) or guide robots using specialized controllers\n\n- Complete diverse tasks ranging from household activities like folding laundry to complex assembly work\n\n- Maintain high standards for data quality and consistency across all demonstrations\n\n- Meet established metrics for data collection volume and quality during your shift\n\nImportant Note: This is a metrics-based role where you'll be expected to meet specific data collection goals throughout your shift. The work involves repetitive task execution, and the quality of data collection is extremely important to our AI training success. Watch some examples of training here: https://drive.google.com/drive/u/0/folders/1YPNYJxKF4i2U41o9pi5AzHCQFYaf2dnw\n\nExample Tasks You'll Train Robots On\n\n- Picking up grocery items and placing them in shipping bags\n\n- Sorting cups, plates, and utensils into bins\n\n- Opening and closing jars of various sizes\n\n- Folding different types of clothing and fabrics\n\n- Installing light bulbs and other simple assembly tasks\n\n- Multi-step electronics assembly processes\n\nAdditional Duties\n\n- Review and annotate videos of robot task performances using computer interfaces\n\n- Provide detailed feedback on robot performance and data quality\n\n- Assist with equipment setup and basic office tasks as needed\n\n- Participate in process improvements to enhance data collection efficiency\n\nPhysical Requirements\n\n- Ability to stand at a workstation for 8-hour shifts\n\n- Full use of both arms and hands for robot control\n\n- Good hand-eye coordination and manual dexterity\n\n- Attention to detail for quality control\n\n\n\nWORK ENVIRONMENT & SCHEDULE\n\nShift Options (8 hours with 30-minute lunch + two paid breaks):\n\n- Morning: 8:00 AM - 4:00 PM PT\n\n- Evening: 4:00 PM - 12:00 AM PT\n\n- Overnight: 12:00 AM -8:00 AM PT\n\n\nShift patterns: Mon-Fri, Wed-Sun, Sat-Wed\n\nCommitment: Minimum 5 days per week\n\nCompensation: $25/hour + benefits package\n\n\n\n\nWHAT WE'RE LOOKING FOR\n\nIdeal Background\n\n- Experience with hands-on technical work, lab environments, or precision tasks\n\n- Interest in AI, robotics, and cutting-edge technology\n\n- Strong attention to detail and quality focus\n\nKey Qualities\n\n- Meticulous attention to detail—data quality is crucial for AI training\n\n- Good manual dexterity and hand-eye coordination\n\n- Enjoys repetitive, precision-focused work\n\n- Thrives in fast-paced, metrics-driven environments\n\n- Excited about contributing to breakthrough AI research\n\n- Collaborative mindset and strong work ethic\n\nNice to Have\n\n- Experience with robotics systems or automation\n\n- Background in manufacturing, assembly, or laboratory work\n\n- Familiarity with AI/ML concepts\n\n- Gaming or simulation experience with controllers\n\n\n\nWHY THIS ROLE MATTERS\n\nYou'll be part of the team building the foundation for general-purpose robotics AI. Every demonstration you provide directly impacts our ability to create robots that can help with household chores, assist in workplaces, and improve quality of life. This is a rare opportunity to work at the cutting edge of AI and robotics while developing valuable technical skills in a rapidly growing field.\n\nReady to help train the robots of tomorrow? We'd love to connect with you!\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"96bc1142-f406-4df3-aaa0-4bcce85f457f","title":"Hardware Systems Intern","department":"Hardware","team":"Hardware","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-04-24T17:26:06.729+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/96bc1142-f406-4df3-aaa0-4bcce85f457f","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/96bc1142-f406-4df3-aaa0-4bcce85f457f/application","descriptionHtml":"<p style=\"min-height:1.5em\">We’re looking for a versatile Hardware Systems Engineering Intern to join our core hardware team this fall. This individual will support the development and improvement of critical infrastructure that supports our fleet’s health and uptime in a demanding 24/7 hardware operation. What happens when you ask a robot to run a dishwasher for 8 hours a day? How hard is it really to make a cup of coffee? You’ll work alongside experienced engineers who are building the systems that enable robots to perform diverse tasks in warehouses as well as uncontrolled environments out in the wild.</p><p style=\"min-height:1.5em\"><strong>The Team</strong></p><p style=\"min-height:1.5em\">The core hardware team sits at the intersection of mechanical, electrical, and systems engineering. They partner closely with software, controls, and manufacturing engineers to take PI’s robots from prototype through production — developing test protocols, diagnosing field failures, and building the infrastructure that keeps the fleet running reliably in warehouses and real-world environments.</p><p style=\"min-height:1.5em\"><strong>In This Role You Will</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Cross-Disciplinary Problem Solving: </strong>Deeply engage with problems at the intersection of mechanical, electrical, and controls for robot hardware — take an ambiguous problem, root-cause it, and design and build a solution that addresses it.</p></li><li><p style=\"min-height:1.5em\"><strong>Reliability Analysis: </strong>Lead data collection and reliability analysis to identify recurring failure modes, log uptime and cycles, and support root-cause investigations (RCCA/FMEA).</p></li><li><p style=\"min-height:1.5em\"><strong>Failure Pareto &amp; System Tracking: </strong>Develop a failure pareto identifying the core issues that cause robots to fail and when. Collaborate with mechanical, electrical, and software engineers to track system performance across builds and deployments.</p></li><li><p style=\"min-height:1.5em\"><strong>Tooling &amp; Process Design: </strong>Build tools, jigs, and architect processes that make the robot fleet faster, safer, and more reliable.</p></li><li><p style=\"min-height:1.5em\"><strong>Test Protocols: </strong>Run and improve test protocols for new hardware releases, field repairs, and after-service verification.</p></li><li><p style=\"min-height:1.5em\"><strong>Build &amp; Production Support: </strong>Support hardware builds and production operations, including tracking inventory, materials, and vendors.</p></li><li><p style=\"min-height:1.5em\"><strong>Configuration &amp; Serialization: </strong>Help implement configuration, serialization, and test tracking systems to enable quick service and replacement of our systems.</p></li></ul><p style=\"min-height:1.5em\"><strong>What We Hope You’ll Bring</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Completed 2B Mechanical or Mechatronics Engineering. Students below 2B with exceptional projects, GitHubs, portfolios, and work experience will also be considered.</p></li><li><p style=\"min-height:1.5em\">Familiarity with power analyzers, oscilloscopes, and debugging of electromechanical systems, with a strong understanding of control systems and communication protocols (CAN, ethernet, high- and low-speed systems).</p></li><li><p style=\"min-height:1.5em\">Basic scripting (Python, Bash) or data visualization experience for fleet analytics.</p></li><li><p style=\"min-height:1.5em\">Exposure to program management tools including Notion and Linear, or the ability to create strong processes with Excel and Google Docs.</p></li><li><p style=\"min-height:1.5em\">Thrive in fast, interdisciplinary environments with tangible outcomes.</p></li></ul><p style=\"min-height:1.5em\"><strong>Bonus Points</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Prior experience with hardware lab, prototype, or production setups — in automotive, consumer electronics, or robotics.</p></li><li><p style=\"min-height:1.5em\">Prior co-op experience in robotics, manufacturing, or product engineering.</p></li></ul><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">The duration of this internship is August-December 2026.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"We’re looking for a versatile Hardware Systems Engineering Intern to join our core hardware team this fall. This individual will support the development and improvement of critical infrastructure that supports our fleet’s health and uptime in a demanding 24/7 hardware operation. What happens when you ask a robot to run a dishwasher for 8 hours a day? How hard is it really to make a cup of coffee? You’ll work alongside experienced engineers who are building the systems that enable robots to perform diverse tasks in warehouses as well as uncontrolled environments out in the wild.\n\nThe Team\n\nThe core hardware team sits at the intersection of mechanical, electrical, and systems engineering. They partner closely with software, controls, and manufacturing engineers to take PI’s robots from prototype through production — developing test protocols, diagnosing field failures, and building the infrastructure that keeps the fleet running reliably in warehouses and real-world environments.\n\nIn This Role You Will\n\n - Cross-Disciplinary Problem Solving: Deeply engage with problems at the intersection of mechanical, electrical, and controls for robot hardware — take an ambiguous problem, root-cause it, and design and build a solution that addresses it.\n\n - Reliability Analysis: Lead data collection and reliability analysis to identify recurring failure modes, log uptime and cycles, and support root-cause investigations (RCCA/FMEA).\n\n - Failure Pareto & System Tracking: Develop a failure pareto identifying the core issues that cause robots to fail and when. Collaborate with mechanical, electrical, and software engineers to track system performance across builds and deployments.\n\n - Tooling & Process Design: Build tools, jigs, and architect processes that make the robot fleet faster, safer, and more reliable.\n\n - Test Protocols: Run and improve test protocols for new hardware releases, field repairs, and after-service verification.\n\n - Build & Production Support: Support hardware builds and production operations, including tracking inventory, materials, and vendors.\n\n - Configuration & Serialization: Help implement configuration, serialization, and test tracking systems to enable quick service and replacement of our systems.\n\nWhat We Hope You’ll Bring\n\n - Completed 2B Mechanical or Mechatronics Engineering. Students below 2B with exceptional projects, GitHubs, portfolios, and work experience will also be considered.\n\n - Familiarity with power analyzers, oscilloscopes, and debugging of electromechanical systems, with a strong understanding of control systems and communication protocols (CAN, ethernet, high- and low-speed systems).\n\n - Basic scripting (Python, Bash) or data visualization experience for fleet analytics.\n\n - Exposure to program management tools including Notion and Linear, or the ability to create strong processes with Excel and Google Docs.\n\n - Thrive in fast, interdisciplinary environments with tangible outcomes.\n\nBonus Points\n\n - Prior experience with hardware lab, prototype, or production setups — in automotive, consumer electronics, or robotics.\n\n - Prior co-op experience in robotics, manufacturing, or product engineering.\n\nThe duration of this internship is August-December 2026.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"f6bee7a7-57ae-4ec1-9276-ae3bcbdc7327","title":"Robotics Software Engineer","department":"Software Engineering","team":"Software Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-01-06T03:37:16.832+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/f6bee7a7-57ae-4ec1-9276-ae3bcbdc7327","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/f6bee7a7-57ae-4ec1-9276-ae3bcbdc7327/application","descriptionHtml":"<p style=\"min-height:1.5em\"><strong>Who We Are</strong></p><p style=\"min-height:1.5em\">Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.</p><p style=\"min-height:1.5em\">Achieving real-world performance requires extremely tight system latency, reliable sensor pipelines, and end-to-end engineering that makes perception and control loops work at real-time speeds.</p><p style=\"min-height:1.5em\">As a Runtime Software Engineer, you’ll engineer the low-latency, high-throughput systems that underpin our physical intelligence model. You won’t be designing ML models - you’ll be the person who makes them <em>run flawlessly in production</em>, optimizing every layer from OS to camera pipeline to networking. You’ll collaborate closely with researchers, platform engineers, and robotics operators to identify bottlenecks and extract maximum performance from the entire system.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>The Team</strong></p><p style=\"min-height:1.5em\">The Runtime team is responsible for building the core platform that Pi’s robots, sensors, and evaluation pipelines rely on. The team spans Linux systems engineering, camera and sensor pipelines, robot actuator controllers, networking, real-time IO, and performance tooling. They ensure our ML models and control systems operate under strict latency budgets and are robust under real-world conditions.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>In This Role You Will</strong></p><p style=\"min-height:1.5em\"><strong>-Own Real-Time Pipelines:</strong> Engineer low-latency, high-reliability sensor and actuator pipelines across Linux, drivers, and middleware.</p><p style=\"min-height:1.5em\"><strong>-Optimize System Performance:</strong> Profile and optimize across compute, I/O, memory, scheduling, networking, and storage to meet real-time constraints and increase throughput.</p><p style=\"min-height:1.5em\"><strong>-Build OS-Level Capabilities:</strong> Extend or modify Linux components, drivers, and scheduling to achieve deterministic behavior under load.</p><p style=\"min-height:1.5em\"><strong>-Streaming &amp; Video Systems:</strong> Develop and optimize real-time video streaming systems where frame timing and packet scheduling matter.</p><p style=\"min-height:1.5em\"><strong>-Reliability &amp; Debugging:</strong> Build tooling for profiling, tracing, and debugging timing issues across distributed systems and hardware interfaces.</p><p style=\"min-height:1.5em\"><strong>-Cross-Functional Collaboration:</strong> Work with researchers, hardware engineers, and operations teams to integrate optimized pipelines into production workflows.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>What We Hope You’ll Bring</strong></p><p style=\"min-height:1.5em\">-Strong programming skills in C++, Rust, or Python, with experience building and optimizing production software.</p><p style=\"min-height:1.5em\">-Experience with Linux systems programming (syscalls, drivers, kernel parameters, scheduling, memory/IO subsystems).</p><p style=\"min-height:1.5em\">-Background in real-time or near–real-time systems, VR/AR, video pipelines, 3D engines, or streaming systems where latency budgets are strict.</p><p style=\"min-height:1.5em\">-Ability to optimize across the entire stack - kernel scheduling, drivers, networking, GPU/CPU workloads, video frameworks, and distributed components.</p><p style=\"min-height:1.5em\">-Experience with profiling tools (perf, tracing, eBPF, GPU profilers, network analyzers) and comfort diving into complex performance issues.</p><p style=\"min-height:1.5em\">-A mindset oriented around determinism, throughput, frame budgets, jitter minimization, and real-time correctness.</p><p style=\"min-height:1.5em\">-Ability to collaborate deeply with researchers and platform engineers to translate high-level model requirements into real-world system performance.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Bonus Points If You Have</strong></p><p style=\"min-height:1.5em\">-Experience with VR/AR platforms or low-latency 3D engines.</p><p style=\"min-height:1.5em\">-Camera system expertise (synchronization, capture pipelines, codecs, GPU offload).</p><p style=\"min-height:1.5em\">-Streaming/video conferencing stack experience (WebRTC, real-time transport optimizations).</p><p style=\"min-height:1.5em\">-Background in robotics, autonomous systems, SLAM pipelines, or perception systems (implementation, not research).</p><p style=\"min-height:1.5em\">-Expertise in kernel-level engineering, device drivers, or high-performance networking.</p><p style=\"min-height:1.5em\">-Familiarity with distributed systems that process real-time data flows.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"Who We Are\n\nPhysical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.\n\nAchieving real-world performance requires extremely tight system latency, reliable sensor pipelines, and end-to-end engineering that makes perception and control loops work at real-time speeds.\n\nAs a Runtime Software Engineer, you’ll engineer the low-latency, high-throughput systems that underpin our physical intelligence model. You won’t be designing ML models - you’ll be the person who makes them run flawlessly in production, optimizing every layer from OS to camera pipeline to networking. You’ll collaborate closely with researchers, platform engineers, and robotics operators to identify bottlenecks and extract maximum performance from the entire system.\n\nThe Team\n\nThe Runtime team is responsible for building the core platform that Pi’s robots, sensors, and evaluation pipelines rely on. The team spans Linux systems engineering, camera and sensor pipelines, robot actuator controllers, networking, real-time IO, and performance tooling. They ensure our ML models and control systems operate under strict latency budgets and are robust under real-world conditions.\n\nIn This Role You Will\n\n-Own Real-Time Pipelines: Engineer low-latency, high-reliability sensor and actuator pipelines across Linux, drivers, and middleware.\n\n-Optimize System Performance: Profile and optimize across compute, I/O, memory, scheduling, networking, and storage to meet real-time constraints and increase throughput.\n\n-Build OS-Level Capabilities: Extend or modify Linux components, drivers, and scheduling to achieve deterministic behavior under load.\n\n-Streaming & Video Systems: Develop and optimize real-time video streaming systems where frame timing and packet scheduling matter.\n\n-Reliability & Debugging: Build tooling for profiling, tracing, and debugging timing issues across distributed systems and hardware interfaces.\n\n-Cross-Functional Collaboration: Work with researchers, hardware engineers, and operations teams to integrate optimized pipelines into production workflows.\n\nWhat We Hope You’ll Bring\n\n-Strong programming skills in C++, Rust, or Python, with experience building and optimizing production software.\n\n-Experience with Linux systems programming (syscalls, drivers, kernel parameters, scheduling, memory/IO subsystems).\n\n-Background in real-time or near–real-time systems, VR/AR, video pipelines, 3D engines, or streaming systems where latency budgets are strict.\n\n-Ability to optimize across the entire stack - kernel scheduling, drivers, networking, GPU/CPU workloads, video frameworks, and distributed components.\n\n-Experience with profiling tools (perf, tracing, eBPF, GPU profilers, network analyzers) and comfort diving into complex performance issues.\n\n-A mindset oriented around determinism, throughput, frame budgets, jitter minimization, and real-time correctness.\n\n-Ability to collaborate deeply with researchers and platform engineers to translate high-level model requirements into real-world system performance.\n\nBonus Points If You Have\n\n-Experience with VR/AR platforms or low-latency 3D engines.\n\n-Camera system expertise (synchronization, capture pipelines, codecs, GPU offload).\n\n-Streaming/video conferencing stack experience (WebRTC, real-time transport optimizations).\n\n-Background in robotics, autonomous systems, SLAM pipelines, or perception systems (implementation, not research).\n\n-Expertise in kernel-level engineering, device drivers, or high-performance networking.\n\n-Familiarity with distributed systems that process real-time data flows.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"c2c1faae-acb6-4c8b-bd0d-e7e180ac8d94","title":"Business Operations","department":"Business","team":"Business","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-02-02T18:01:04.048+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/c2c1faae-acb6-4c8b-bd0d-e7e180ac8d94","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/c2c1faae-acb6-4c8b-bd0d-e7e180ac8d94/application","descriptionHtml":"<p style=\"min-height:1.5em\"><strong>Who We Are</strong></p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">As the company scales, success increasingly depends not just on research excellence, but on strong business execution - across partnerships, operations, infrastructure, and deployment.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Success in this role looks like independently identifying the highest-leverage problems, structuring them into executable plans, and driving them to measurable outcomes with minimal founder involvement.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>The Team</strong></p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">This role sits close to the founders and works cross-functionally with research, engineering, operations, finance, legal, and external partners. There is no single “lane”, the mandate is to add leverage wherever the company most needs it.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>In This Role You Will</strong></p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">-Own and execute cross-functional projects with high ambiguity and real business impact.</p><p style=\"min-height:1.5em\">-Drive data, compute, and infrastructure partnerships, from sourcing through negotiation and management.</p><p style=\"min-height:1.5em\">-Plug into deployment efforts: sourcing opportunities, structuring contracts, pricing, and operational setup.</p><p style=\"min-height:1.5em\">-Assist with and drive internal scaling initiatives such as office expansion, international operations, and company planning.</p><p style=\"min-height:1.5em\">-Support investor, board, and external communications including decks, analyses, and prep.</p><p style=\"min-height:1.5em\">-Act as an execution arm for founders and leaders, translating priorities into outcomes.</p><p style=\"min-height:1.5em\"><strong><br /></strong></p><p style=\"min-height:1.5em\"><strong>What We Hope You’ll Bring</strong></p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">-Strong analytical and strategic instincts with a bias toward action.</p><p style=\"min-height:1.5em\">-Comfort operating independently in ambiguous environments.</p><p style=\"min-height:1.5em\">-Commercial mindset and basic financial fluency (contracts, pricing, tradeoffs).</p><p style=\"min-height:1.5em\">-Exceptional written and verbal communication.</p><p style=\"min-height:1.5em\">-Willingness to do anything, paired with strong prioritization instincts and comfort pushing back when work is low-leverage.</p><p style=\"min-height:1.5em\">-Strong π-fit: respect for research and engineering culture, curiosity, and intellectual humility.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Bonus Points If You Have</strong></p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">-Background in consulting, venture capital, private equity, or finance.</p><p style=\"min-height:1.5em\">-Experience negotiating vendor, data, or infrastructure agreements.</p><p style=\"min-height:1.5em\">-Exposure to startups that have scaled quickly or inflected suddenly.</p><p style=\"min-height:1.5em\">-International operations or cross-border project experience.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"Who We Are\n\nPhysical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.\n\nAs the company scales, success increasingly depends not just on research excellence, but on strong business execution - across partnerships, operations, infrastructure, and deployment.\n\nSuccess in this role looks like independently identifying the highest-leverage problems, structuring them into executable plans, and driving them to measurable outcomes with minimal founder involvement.\n\nThe Team\n\nThis role sits close to the founders and works cross-functionally with research, engineering, operations, finance, legal, and external partners. There is no single “lane”, the mandate is to add leverage wherever the company most needs it.\n\nIn This Role You Will\n\n-Own and execute cross-functional projects with high ambiguity and real business impact.\n\n-Drive data, compute, and infrastructure partnerships, from sourcing through negotiation and management.\n\n-Plug into deployment efforts: sourcing opportunities, structuring contracts, pricing, and operational setup.\n\n-Assist with and drive internal scaling initiatives such as office expansion, international operations, and company planning.\n\n-Support investor, board, and external communications including decks, analyses, and prep.\n\n-Act as an execution arm for founders and leaders, translating priorities into outcomes.\n\n\n\n\nWhat We Hope You’ll Bring\n\n-Strong analytical and strategic instincts with a bias toward action.\n\n-Comfort operating independently in ambiguous environments.\n\n-Commercial mindset and basic financial fluency (contracts, pricing, tradeoffs).\n\n-Exceptional written and verbal communication.\n\n-Willingness to do anything, paired with strong prioritization instincts and comfort pushing back when work is low-leverage.\n\n-Strong π-fit: respect for research and engineering culture, curiosity, and intellectual humility.\n\nBonus Points If You Have\n\n-Background in consulting, venture capital, private equity, or finance.\n\n-Experience negotiating vendor, data, or infrastructure agreements.\n\n-Exposure to startups that have scaled quickly or inflected suddenly.\n\n-International operations or cross-border project experience.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"c8f9e9aa-8801-4916-9b1f-2c0bd5f072f9","title":"Controls Engineer","department":"Software Engineering","team":"Software Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-01-07T20:16:15.835+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/c8f9e9aa-8801-4916-9b1f-2c0bd5f072f9","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/c8f9e9aa-8801-4916-9b1f-2c0bd5f072f9/application","descriptionHtml":"<p style=\"min-height:1.5em\">As a Controls Engineer, you will design and implement the algorithms that make PI’s robots behave predictably, smoothly, and safely under varied and uncertain conditions.</p><p style=\"min-height:1.5em\"><strong>The Team</strong></p><p style=\"min-height:1.5em\">The Controls team builds and tunes the core feedback and model-based algorithms, real-time loops, simulations, and actuator/sensor subsystems that make PI’s robots stable and reliable. They work closely with research, hardware, and operations to debug complex system behaviors and ensure our learning-based systems operate under strict real-time constraints in unpredictable environments.</p><p style=\"min-height:1.5em\"><strong>In This Role You Will</strong></p><p style=\"min-height:1.5em\"><strong>-Design &amp; implement control algorithms: </strong>PID, LQR, MPC, inverse dynamics, and feedforward controllers.</p><p style=\"min-height:1.5em\"><strong>-Build &amp; validate models: </strong>Create and refine physical and inverse dynamics models for simulation and control design.</p><p style=\"min-height:1.5em\"><strong>-Develop real-time loops: </strong>Write and optimize runtime control loops, including neural-network-driven control.</p><p style=\"min-height:1.5em\"><strong>-Own robotic bring-up: </strong>Integrate and tune arms, mobile bases, teleop systems, and full-body platforms.</p><p style=\"min-height:1.5em\"><strong>-Debug complex system behaviors: </strong>Diagnose and resolve hardware/software/runtime issues using first-principles reasoning.</p><p style=\"min-height:1.5em\"><strong>-Build sensor/actuator subsystems: </strong>Work with embedded systems, drivers, and communication protocols (CAN, SPI, I2C, Ethernet).</p><p style=\"min-height:1.5em\"><strong>-Partner cross-functionally:</strong> Work with researchers, platform engineers, and operators to ensure stable, predictable real-world behavior.</p><p style=\"min-height:1.5em\"><strong>-Support R&amp;D: </strong>Prototype configurations, collect structured datasets, and iterate directly with researchers.</p><p style=\"min-height:1.5em\"><strong>What We Hope You’ll Bring</strong></p><p style=\"min-height:1.5em\">-Deep understanding of model-based control algorithms and inverse dynamics</p><p style=\"min-height:1.5em\">-Ability to validate control approaches in simulation and translate them to real hardware</p><p style=\"min-height:1.5em\">-Proficiency in Python and C++, including firmware-adjacent development</p><p style=\"min-height:1.5em\">-Skill in writing and tuning real-time control loops</p><p style=\"min-height:1.5em\">-Hands-on capability to debug electromechanical systems end-to-end</p><p style=\"min-height:1.5em\">-Familiarity with embedded communication protocols (CAN, SPI, I2C, Ethernet)</p><p style=\"min-height:1.5em\">-Clear communication with researchers, hardware teams, and operators</p><p style=\"min-height:1.5em\">-A structured, collaborative approach to solving complex system issues</p><p style=\"min-height:1.5em\"><strong>Bonus Points If You Have</strong></p><p style=\"min-height:1.5em\">-Background in manipulation or mobile robotic platforms</p><p style=\"min-height:1.5em\">-Exposure to robot learning or integrating learned policies into control stacks</p><p style=\"min-height:1.5em\">-Ability to design or refine custom actuator or sensor hardware</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"As a Controls Engineer, you will design and implement the algorithms that make PI’s robots behave predictably, smoothly, and safely under varied and uncertain conditions.\n\nThe Team\n\nThe Controls team builds and tunes the core feedback and model-based algorithms, real-time loops, simulations, and actuator/sensor subsystems that make PI’s robots stable and reliable. They work closely with research, hardware, and operations to debug complex system behaviors and ensure our learning-based systems operate under strict real-time constraints in unpredictable environments.\n\nIn This Role You Will\n\n-Design & implement control algorithms: PID, LQR, MPC, inverse dynamics, and feedforward controllers.\n\n-Build & validate models: Create and refine physical and inverse dynamics models for simulation and control design.\n\n-Develop real-time loops: Write and optimize runtime control loops, including neural-network-driven control.\n\n-Own robotic bring-up: Integrate and tune arms, mobile bases, teleop systems, and full-body platforms.\n\n-Debug complex system behaviors: Diagnose and resolve hardware/software/runtime issues using first-principles reasoning.\n\n-Build sensor/actuator subsystems: Work with embedded systems, drivers, and communication protocols (CAN, SPI, I2C, Ethernet).\n\n-Partner cross-functionally: Work with researchers, platform engineers, and operators to ensure stable, predictable real-world behavior.\n\n-Support R&D: Prototype configurations, collect structured datasets, and iterate directly with researchers.\n\nWhat We Hope You’ll Bring\n\n-Deep understanding of model-based control algorithms and inverse dynamics\n\n-Ability to validate control approaches in simulation and translate them to real hardware\n\n-Proficiency in Python and C++, including firmware-adjacent development\n\n-Skill in writing and tuning real-time control loops\n\n-Hands-on capability to debug electromechanical systems end-to-end\n\n-Familiarity with embedded communication protocols (CAN, SPI, I2C, Ethernet)\n\n-Clear communication with researchers, hardware teams, and operators\n\n-A structured, collaborative approach to solving complex system issues\n\nBonus Points If You Have\n\n-Background in manipulation or mobile robotic platforms\n\n-Exposure to robot learning or integrating learned policies into control stacks\n\n-Ability to design or refine custom actuator or sensor hardware\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"0bcf909e-b38b-4276-91a1-e55c4c56a33a","title":"Mechatronics Intern","department":"Hardware","team":"Hardware","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-04-24T17:49:43.487+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/0bcf909e-b38b-4276-91a1-e55c4c56a33a","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/0bcf909e-b38b-4276-91a1-e55c4c56a33a/application","descriptionHtml":"<p style=\"min-height:1.5em\">Fundamentally, a builder. Someone who loves to make robots real. We want someone who’s as comfortable debugging a CAN bus issue as they are machining a bracket — an individual who thinks in systems, and who gets excited by tight integration between mechanical, electrical, and embedded design. This fall, you’ll join the core Hardware Engineering team at Physical Intelligence who is supporting the robots that power PI’s data collection and model training operations.</p><p style=\"min-height:1.5em\"><strong>The Team</strong></p><p style=\"min-height:1.5em\">The core Hardware Engineering team designs and builds the robotic arms, mobile platforms, and end-effectors that underpin PI’s data collection and model training operations. They work across mechanical, electrical, embedded, and software disciplines to iterate quickly on prototypes, bring up new subsystems, and keep the fleet performant in real-world environments.</p><p style=\"min-height:1.5em\"><strong>In This Role You Will</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Subsystem Design &amp; Test: </strong>Design, build, and test key subsystems for various robotic arms and mobile platforms — including actuation, sensing, enclosures, and power systems.</p></li><li><p style=\"min-height:1.5em\"><strong>Hands-On Prototyping: </strong>Work hands-on with prototypes in our hardware lab, including bring-up, assembly, calibration, and reliability testing of arms, lifts, mobile bases, and end-effectors.</p></li><li><p style=\"min-height:1.5em\"><strong>Cross-Disciplinary Integration: </strong>Integrate cross-disciplinary inputs from mechanical, electrical, and software teams to root-cause mission-critical issues and drive high-level system performance.</p></li><li><p style=\"min-height:1.5em\"><strong>Data-Driven Iteration: </strong>Analyze data from deployments to inform design iteration and reliability improvements.</p></li><li><p style=\"min-height:1.5em\"><strong>Full-Stack Subsystem Ownership: </strong>Own the full stack of a subsystem from CAD to PCB to bench testing.</p></li></ul><p style=\"min-height:1.5em\"><strong>What We Hope You’ll Bring</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Completed 3A Mechanical or Mechatronics Engineering. Students below 3A with exceptional projects, GitHubs, portfolios, and work experience will also be considered.</p></li><li><p style=\"min-height:1.5em\">Strong mechanical and electromechanical design fundamentals (dynamic loading, FEA, DFM).</p></li><li><p style=\"min-height:1.5em\">Familiarity with embedded and mechatronic systems (CAN, BLDC control, motor controllers).</p></li><li><p style=\"min-height:1.5em\">Proficiency in CAD (NX, OnShape, SolidWorks) and rapid prototyping tools (3D printing — SLA and FDM — laser cutting).</p></li><li><p style=\"min-height:1.5em\">Basic electrical design and debug (schematics, soldering, test equipment).</p></li><li><p style=\"min-height:1.5em\">Data-driven debugging and test planning (Python, MATLAB, or similar).</p></li></ul><p style=\"min-height:1.5em\"><strong>Bonus Points</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Exposure to manufacturing or assembly environments.</p></li><li><p style=\"min-height:1.5em\">Prior experience in robotics, autonomous systems, or hardware startups.</p></li></ul><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">The duration of this internship is August-December 2026.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"Fundamentally, a builder. Someone who loves to make robots real. We want someone who’s as comfortable debugging a CAN bus issue as they are machining a bracket — an individual who thinks in systems, and who gets excited by tight integration between mechanical, electrical, and embedded design. This fall, you’ll join the core Hardware Engineering team at Physical Intelligence who is supporting the robots that power PI’s data collection and model training operations.\n\nThe Team\n\nThe core Hardware Engineering team designs and builds the robotic arms, mobile platforms, and end-effectors that underpin PI’s data collection and model training operations. They work across mechanical, electrical, embedded, and software disciplines to iterate quickly on prototypes, bring up new subsystems, and keep the fleet performant in real-world environments.\n\nIn This Role You Will\n\n - Subsystem Design & Test: Design, build, and test key subsystems for various robotic arms and mobile platforms — including actuation, sensing, enclosures, and power systems.\n\n - Hands-On Prototyping: Work hands-on with prototypes in our hardware lab, including bring-up, assembly, calibration, and reliability testing of arms, lifts, mobile bases, and end-effectors.\n\n - Cross-Disciplinary Integration: Integrate cross-disciplinary inputs from mechanical, electrical, and software teams to root-cause mission-critical issues and drive high-level system performance.\n\n - Data-Driven Iteration: Analyze data from deployments to inform design iteration and reliability improvements.\n\n - Full-Stack Subsystem Ownership: Own the full stack of a subsystem from CAD to PCB to bench testing.\n\nWhat We Hope You’ll Bring\n\n - Completed 3A Mechanical or Mechatronics Engineering. Students below 3A with exceptional projects, GitHubs, portfolios, and work experience will also be considered.\n\n - Strong mechanical and electromechanical design fundamentals (dynamic loading, FEA, DFM).\n\n - Familiarity with embedded and mechatronic systems (CAN, BLDC control, motor controllers).\n\n - Proficiency in CAD (NX, OnShape, SolidWorks) and rapid prototyping tools (3D printing — SLA and FDM — laser cutting).\n\n - Basic electrical design and debug (schematics, soldering, test equipment).\n\n - Data-driven debugging and test planning (Python, MATLAB, or similar).\n\nBonus Points\n\n - Exposure to manufacturing or assembly environments.\n\n - Prior experience in robotics, autonomous systems, or hardware startups.\n\nThe duration of this internship is August-December 2026.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"567d620f-7600-4e35-9edd-f41ed4db45ce","title":"Forward Deployed Robotics Engineer","department":"Hardware","team":"Hardware","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2025-11-17T21:36:46.127+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/567d620f-7600-4e35-9edd-f41ed4db45ce","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/567d620f-7600-4e35-9edd-f41ed4db45ce/application","descriptionHtml":"<h3><strong>Role Overview</strong></h3><p style=\"min-height:1.5em\">As a <strong>Forward Deployed Robotics Engineer</strong>, you'll serve as the first line of technical defense for our growing fleet of robotic systems deployed across warehouse and external data-collection environments. Our diverse robot fleet—including both static and mobile systems—performs complex manipulation and sensing tasks in real-world settings. When issues arise, you'll be the first responder: analyzing field tickets, reproducing issues, gathering diagnostic data, and driving resolution to ensure maximum fleet uptime.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Key Responsibilities</strong></p><p style=\"min-height:1.5em\"><strong>- Primary Robot Fleet Issue Technical Triage Point</strong>: Manage incoming fleet issue ticket queue, prioritize based on fleet-wide implications and operational goals, and triage as hardware, software, or operational issue.</p><p style=\"min-height:1.5em\"><strong>- Fast-Paced Operations</strong>: Handle quick turnaround expectations while maintaining diagnostic quality</p><p style=\"min-height:1.5em\"><strong>- On-Site Diagnostics</strong>: Perform physical inspections and functional tests at robot stations to verify issue reproduction</p><p style=\"min-height:1.5em\"><strong>- Data Analysis</strong>: Analyze telemetry, sensor data, and logs to form and test hypotheses about root causes</p><p style=\"min-height:1.5em\"><strong> - Failure Analysis</strong>: Execute technically sound Failure Analysis / Root Cause Analysis procedures</p><p style=\"min-height:1.5em\"><strong>- Cross-Team Collaboration</strong>: Partner with hardware and software teams to reproduce and resolve complex issues</p><p style=\"min-height:1.5em\"><strong>- Pattern Recognition</strong>: Identify recurring issues across the fleet and surface reliability insights for design improvements</p><p style=\"min-height:1.5em\"><strong>- Documentation</strong>: Maintain clear, traceable documentation for every diagnostic and escalation event</p><p style=\"min-height:1.5em\"><strong>- Metrics &amp; Reporting</strong>: Track and report issue trends and fleet health metrics to leadership</p><p style=\"min-height:1.5em\"><strong>- Process Improvement</strong>: Collaborate with team lead to develop and maintain diagnostic procedures and troubleshooting guides</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Required Competencies &amp; Skills</strong></p><p style=\"min-height:1.5em\"><strong>- Education</strong>: B.S. in Robotics, Mechatronics, Systems Engineering, or equivalent experience</p><p style=\"min-height:1.5em\"><strong>- Hardware Knowledge</strong>: Proficiency debugging electromechanical systems including actuators, PCBs, cameras, wiring harnesses, and communication hardware</p><p style=\"min-height:1.5em\"><strong>- Software Knowledge:</strong> Experience with log parsing and basic scripting for diagnostics (Python or Bash)</p><p style=\"min-height:1.5em\"><strong>- Systems Knowledge</strong>: Strong understanding of mechanical, electrical, and software interactions in robotic systems</p><p style=\"min-height:1.5em\"><strong>- Communication</strong>: Excellent written and verbal communication, particularly in technical documentation and shift handoffs</p><p style=\"min-height:1.5em\"><strong>- Hands-On Problem Solving Experience:</strong> Minimum 2 years work experience with debugging and completing root cause investigations of systems with hardware and software issues</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Strongly Preferred:</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience supporting multi-robot fleets, warehouse automation systems, or field robotics deployments</p></li></ul><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><em>Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</em></p>","descriptionPlain":"ROLE OVERVIEW\n\nAs a Forward Deployed Robotics Engineer, you'll serve as the first line of technical defense for our growing fleet of robotic systems deployed across warehouse and external data-collection environments. Our diverse robot fleet—including both static and mobile systems—performs complex manipulation and sensing tasks in real-world settings. When issues arise, you'll be the first responder: analyzing field tickets, reproducing issues, gathering diagnostic data, and driving resolution to ensure maximum fleet uptime.\n\nKey Responsibilities\n\n- Primary Robot Fleet Issue Technical Triage Point: Manage incoming fleet issue ticket queue, prioritize based on fleet-wide implications and operational goals, and triage as hardware, software, or operational issue.\n\n- Fast-Paced Operations: Handle quick turnaround expectations while maintaining diagnostic quality\n\n- On-Site Diagnostics: Perform physical inspections and functional tests at robot stations to verify issue reproduction\n\n- Data Analysis: Analyze telemetry, sensor data, and logs to form and test hypotheses about root causes\n\n- Failure Analysis: Execute technically sound Failure Analysis / Root Cause Analysis procedures\n\n- Cross-Team Collaboration: Partner with hardware and software teams to reproduce and resolve complex issues\n\n- Pattern Recognition: Identify recurring issues across the fleet and surface reliability insights for design improvements\n\n- Documentation: Maintain clear, traceable documentation for every diagnostic and escalation event\n\n- Metrics & Reporting: Track and report issue trends and fleet health metrics to leadership\n\n- Process Improvement: Collaborate with team lead to develop and maintain diagnostic procedures and troubleshooting guides\n\nRequired Competencies & Skills\n\n- Education: B.S. in Robotics, Mechatronics, Systems Engineering, or equivalent experience\n\n- Hardware Knowledge: Proficiency debugging electromechanical systems including actuators, PCBs, cameras, wiring harnesses, and communication hardware\n\n- Software Knowledge: Experience with log parsing and basic scripting for diagnostics (Python or Bash)\n\n- Systems Knowledge: Strong understanding of mechanical, electrical, and software interactions in robotic systems\n\n- Communication: Excellent written and verbal communication, particularly in technical documentation and shift handoffs\n\n- Hands-On Problem Solving Experience: Minimum 2 years work experience with debugging and completing root cause investigations of systems with hardware and software issues\n\nStrongly Preferred:\n\n - Experience supporting multi-robot fleets, warehouse automation systems, or field robotics deployments\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"f70f9481-ea7e-48e4-9212-f9c10952a028","title":"Build & Release Engineer","department":"Software Engineering","team":"Software Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-04-29T17:00:23.707+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/f70f9481-ea7e-48e4-9212-f9c10952a028","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/f70f9481-ea7e-48e4-9212-f9c10952a028/application","descriptionHtml":"<p style=\"min-height:1.5em\">As a Build &amp; Release Engineer, you will own the infrastructure and developer platforms that underpin our engineering workflows. This includes GitHub-based CI/CD pipelines, Bazel build and test systems, cloud infrastructure, and Kubernetes services that allow engineers to ship reliably at scale.</p><p style=\"min-height:1.5em\">This is a senior, hands-on infrastructure role focused on developer productivity, build reliability, and operational scale.</p><p style=\"min-height:1.5em\"><strong>The Team</strong></p><p style=\"min-height:1.5em\">The Operations and Infrastructure teams support the real-world deployment and iteration of PI’s robotics systems. They are responsible for the platforms, tooling, and cloud environments that enable engineers to build, test, and deploy reliably. This includes ownership of GitHub workflows, CI systems, and build tooling that sit directly on the critical path of development.</p><p style=\"min-height:1.5em\"><strong>In This Role You Will</strong></p><p style=\"min-height:1.5em\"><strong>- CI/CD Ownership: </strong>Design and operate GitHub-based CI/CD systems (GitHub Actions, checks, workflows) with a focus on reliability, speed, and signal quality.</p><p style=\"min-height:1.5em\"><strong>- Build Systems: </strong>Own and evolve Bazel-based build and test infrastructure that supports C++, Python, Rust, and Typescript-based development.</p><p style=\"min-height:1.5em\"><strong>- Infrastructure Engineering: </strong>Build and maintain Kubernetes-based services and cloud infrastructure using Terraform and infrastructure-as-code.</p><p style=\"min-height:1.5em\"><strong>- Automation &amp; Self-Service: </strong>Replace manual release, provisioning, and access workflows with automated, GitHub-integrated systems.</p><p style=\"min-height:1.5em\"><strong>- Reliability &amp; Throughput: </strong>Reduce flaky builds, failed deploys, and CI bottlenecks that slow engineering velocity.</p><p style=\"min-height:1.5em\"><strong>- Cross-Team Enablement:</strong> Partner with engineers across the stack to make builds, tests, and deploys predictable and fast.</p><p style=\"min-height:1.5em\"><strong>What We Hope You’ll Bring</strong></p><p style=\"min-height:1.5em\">- Strong experience operating GitHub-centric development workflows at scale.</p><p style=\"min-height:1.5em\">- Deep familiarity with CI/CD systems and build reliability challenges.</p><p style=\"min-height:1.5em\">- Experience with Bazel or similar large-scale build systems.</p><p style=\"min-height:1.5em\">- Proficiency in cloud infrastructure, Kubernetes, and Terraform.</p><p style=\"min-height:1.5em\">- Strong instincts for developer experience and operational leverage.</p><p style=\"min-height:1.5em\"><strong>Bonus Points If You Have</strong></p><p style=\"min-height:1.5em\">- Experience improving CI throughput for hundreds of engineers.</p><p style=\"min-height:1.5em\">- Expertise in Bazel optimization (remote caching, test sharding, incremental builds).</p><p style=\"min-height:1.5em\">- Security- or InfoSec-adjacent infrastructure automation.</p><p style=\"min-height:1.5em\">- Background in internal developer productivity or platform teams.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"As a Build & Release Engineer, you will own the infrastructure and developer platforms that underpin our engineering workflows. This includes GitHub-based CI/CD pipelines, Bazel build and test systems, cloud infrastructure, and Kubernetes services that allow engineers to ship reliably at scale.\n\nThis is a senior, hands-on infrastructure role focused on developer productivity, build reliability, and operational scale.\n\nThe Team\n\nThe Operations and Infrastructure teams support the real-world deployment and iteration of PI’s robotics systems. They are responsible for the platforms, tooling, and cloud environments that enable engineers to build, test, and deploy reliably. This includes ownership of GitHub workflows, CI systems, and build tooling that sit directly on the critical path of development.\n\nIn This Role You Will\n\n- CI/CD Ownership: Design and operate GitHub-based CI/CD systems (GitHub Actions, checks, workflows) with a focus on reliability, speed, and signal quality.\n\n- Build Systems: Own and evolve Bazel-based build and test infrastructure that supports C++, Python, Rust, and Typescript-based development.\n\n- Infrastructure Engineering: Build and maintain Kubernetes-based services and cloud infrastructure using Terraform and infrastructure-as-code.\n\n- Automation & Self-Service: Replace manual release, provisioning, and access workflows with automated, GitHub-integrated systems.\n\n- Reliability & Throughput: Reduce flaky builds, failed deploys, and CI bottlenecks that slow engineering velocity.\n\n- Cross-Team Enablement: Partner with engineers across the stack to make builds, tests, and deploys predictable and fast.\n\nWhat We Hope You’ll Bring\n\n- Strong experience operating GitHub-centric development workflows at scale.\n\n- Deep familiarity with CI/CD systems and build reliability challenges.\n\n- Experience with Bazel or similar large-scale build systems.\n\n- Proficiency in cloud infrastructure, Kubernetes, and Terraform.\n\n- Strong instincts for developer experience and operational leverage.\n\nBonus Points If You Have\n\n- Experience improving CI throughput for hundreds of engineers.\n\n- Expertise in Bazel optimization (remote caching, test sharding, incremental builds).\n\n- Security- or InfoSec-adjacent infrastructure automation.\n\n- Background in internal developer productivity or platform teams.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"bb72d6bc-631e-423b-bc06-be225105d73d","title":"Robot Test Engineer","department":"Hardware","team":"Hardware","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-01-22T06:03:02.208+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/bb72d6bc-631e-423b-bc06-be225105d73d","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/bb72d6bc-631e-423b-bc06-be225105d73d/application","descriptionHtml":"<h3><strong>Role Overview</strong></h3><p style=\"min-height:1.5em\">As a <strong>Robot Test Engineer</strong>, your role is critical to ensuring that robot systems integrating into our growing robot fleet meet performance requirements and are reliable. You will work with robot systems across a range of maturity levels from early prototypes to production systems. You will be responsible for creating test systems and test processes/documentation, executing tests on robotic systems, and engaging with members of the hardware engineering and software engineering teams to resolve issues that arise during test.</p><h3><strong>Key Responsibilities</strong></h3><p style=\"min-height:1.5em\"><strong>- Test Process Development:</strong> Create test processes and documentation for robotic systems.</p><p style=\"min-height:1.5em\"><strong>- Test Setup Development:</strong> Build and maintain robot test systems, explore ways to automate testing, etc.</p><p style=\"min-height:1.5em\"><strong>- Test Execution:</strong> Complete functional, environmental, and reliability testing of robot systems, assemblies, and components ranging across different maturity levels from early prototypes to production robot systems. Collect data, analyze data, and compile data into reports to communicate results broadly.</p><p style=\"min-height:1.5em\"><strong>- Test Failure Investigation:</strong> Perform root cause analysis from test failures and work with engineers to resolve and drive corrective actions.</p><p style=\"min-height:1.5em\"><strong>- Cross Functional Collaboration:</strong> Engage with hardware and software teams to align on test processes and to resolve issues observed during testing.</p><p style=\"min-height:1.5em\"></p><h3><strong>Required Competencies &amp; Skills</strong></h3><p style=\"min-height:1.5em\"><strong>- Education</strong>: B.S. in Robotics, Mechatronics, Systems Engineering, Electrical Engineering or equivalent experience</p><p style=\"min-height:1.5em\">- <strong>Experience:</strong> 4+ years of hands on experience in hardware test engineering, product validation, or quality assurance for electromechanical or robotics systems</p><p style=\"min-height:1.5em\"><strong>- Hardware Knowledge</strong>: Proficiency debugging electromechanical systems including actuators, PCBs, cameras, wiring harnesses, and communication hardware.</p><p style=\"min-height:1.5em\"><strong>- Systems Knowledge</strong>: Strong understanding of mechanical, electrical, and software interactions in robotic systems</p><p style=\"min-height:1.5em\"><strong>- Software Knowledge:</strong> Basic scripting to understand robot testing code development from runtime/robot software team.</p><p style=\"min-height:1.5em\"><strong>- Data Analysis &amp; Processing:</strong> Ability to process data (i.e. Excel, Matlab, Python, etc.) to analyze and create graphics.</p><p style=\"min-height:1.5em\"><strong>- Hands on Skills: B</strong>uilding test fixtures, performing diagnostics, and using standard lab equipment (oscilloscopes, multimeters, environmental chambers, etc.)</p><p style=\"min-height:1.5em\">- <strong>Strong Communication</strong>: Excellent written and verbal communication, particularly in technical documentation.</p><p style=\"min-height:1.5em\"><strong>- Other Facets:</strong> High attention to detail, highly organized, capable of supporting multiple test campaigns in parallel, ability to work in a highly dynamic start up environment (adaptable/not rigid to specific test standards). </p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"ROLE OVERVIEW\n\nAs a Robot Test Engineer, your role is critical to ensuring that robot systems integrating into our growing robot fleet meet performance requirements and are reliable. You will work with robot systems across a range of maturity levels from early prototypes to production systems. You will be responsible for creating test systems and test processes/documentation, executing tests on robotic systems, and engaging with members of the hardware engineering and software engineering teams to resolve issues that arise during test.\n\n\nKEY RESPONSIBILITIES\n\n- Test Process Development: Create test processes and documentation for robotic systems.\n\n- Test Setup Development: Build and maintain robot test systems, explore ways to automate testing, etc.\n\n- Test Execution: Complete functional, environmental, and reliability testing of robot systems, assemblies, and components ranging across different maturity levels from early prototypes to production robot systems. Collect data, analyze data, and compile data into reports to communicate results broadly.\n\n- Test Failure Investigation: Perform root cause analysis from test failures and work with engineers to resolve and drive corrective actions.\n\n- Cross Functional Collaboration: Engage with hardware and software teams to align on test processes and to resolve issues observed during testing.\n\n\nREQUIRED COMPETENCIES & SKILLS\n\n- Education: B.S. in Robotics, Mechatronics, Systems Engineering, Electrical Engineering or equivalent experience\n\n- Experience: 4+ years of hands on experience in hardware test engineering, product validation, or quality assurance for electromechanical or robotics systems\n\n- Hardware Knowledge: Proficiency debugging electromechanical systems including actuators, PCBs, cameras, wiring harnesses, and communication hardware.\n\n- Systems Knowledge: Strong understanding of mechanical, electrical, and software interactions in robotic systems\n\n- Software Knowledge: Basic scripting to understand robot testing code development from runtime/robot software team.\n\n- Data Analysis & Processing: Ability to process data (i.e. Excel, Matlab, Python, etc.) to analyze and create graphics.\n\n- Hands on Skills: Building test fixtures, performing diagnostics, and using standard lab equipment (oscilloscopes, multimeters, environmental chambers, etc.)\n\n- Strong Communication: Excellent written and verbal communication, particularly in technical documentation.\n\n- Other Facets: High attention to detail, highly organized, capable of supporting multiple test campaigns in parallel, ability to work in a highly dynamic start up environment (adaptable/not rigid to specific test standards).\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"4e547c5a-e4ee-40a7-b14b-c4daf9c072eb","title":"ML Infra Engineer (TPU/Jax/Optimization)","department":"Machine Learning","team":"Machine Learning","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-01-23T20:49:10.281+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/4e547c5a-e4ee-40a7-b14b-c4daf9c072eb","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/4e547c5a-e4ee-40a7-b14b-c4daf9c072eb/application","descriptionHtml":"<p style=\"min-height:1.5em\">In this role you will help scale and optimize our training systems and core model code. You’ll own critical infrastructure for large-scale training, from managing GPU/TPU compute and job orchestration to building reusable and efficient JAX training pipelines. You’ll work closely with researchers and model engineers to translate ideas into experiments—and those experiments into production training runs.</p><p style=\"min-height:1.5em\">This is a hands-on, high-leverage role at the intersection of ML, software engineering, and scalable infrastructure.</p><h3><strong>The Team</strong></h3><p style=\"min-height:1.5em\">The ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. The team works closely with research, data, and platform engineers to ensure models can scale from prototype to production-grade training runs.</p><h3><strong>In This Role You Will</strong></h3><p style=\"min-height:1.5em\"><strong>- Own training/inference infrastructure:</strong> Design, implement, and maintain systems for large-scale model training, including scheduling, job management, checkpointing, and metrics/logging.</p><p style=\"min-height:1.5em\"><strong>- Scale distributed training:</strong> Work with researchers to scale JAX-based training across TPU and GPU clusters with minimal friction.</p><p style=\"min-height:1.5em\"><strong>- Optimize performance:</strong> Profile and improve memory usage, device utilization, throughput, and distributed synchronization.</p><p style=\"min-height:1.5em\"><strong>- Enable rapid iteration: </strong>Build abstractions for launching, monitoring, debugging, and reproducing experiments.</p><p style=\"min-height:1.5em\"><strong>- Manage compute resources:</strong> Ensure efficient allocation and utilization of cloud-based GPU/TPU compute while controlling cost.</p><p style=\"min-height:1.5em\"><strong>- Partner with researchers: </strong>Translate research needs into infra capabilities and guide best practices for training at scale.</p><p style=\"min-height:1.5em\"><strong>- Contribute to core training code:</strong> Evolve JAX model and training code to support new architectures, modalities, and evaluation metrics.</p><h3><strong>What We Hope You’ll Bring</strong></h3><p style=\"min-height:1.5em\">- Strong software engineering fundamentals and experience building ML training infrastructure or internal platforms.</p><p style=\"min-height:1.5em\">- Hands-on large-scale training experience in JAX (preferred), PyTorch.</p><p style=\"min-height:1.5em\">- Familiarity with distributed training, multi-host setups, data loaders, and evaluation pipelines.</p><p style=\"min-height:1.5em\">- Experience managing training workloads on cloud platforms (e.g., SLURM, Kubernetes, GCP TPU/GKE, AWS).</p><p style=\"min-height:1.5em\">- Ability to debug and optimize performance bottlenecks across the training stack.</p><p style=\"min-height:1.5em\">- Strong cross-functional communication and ownership mindset.</p><h3><strong>Bonus Points If You Have</strong></h3><p style=\"min-height:1.5em\">- Deep ML systems background (e.g., training compilers, runtime optimization, custom kernels).</p><p style=\"min-height:1.5em\">- Experience operating close to hardware (GPU/TPU performance tuning).</p><p style=\"min-height:1.5em\">- Background in robotics, multimodal models, or large-scale foundation models.</p><p style=\"min-height:1.5em\">- Experience designing abstractions that balance researcher flexibility with system reliability.</p>","descriptionPlain":"In this role you will help scale and optimize our training systems and core model code. You’ll own critical infrastructure for large-scale training, from managing GPU/TPU compute and job orchestration to building reusable and efficient JAX training pipelines. You’ll work closely with researchers and model engineers to translate ideas into experiments—and those experiments into production training runs.\n\nThis is a hands-on, high-leverage role at the intersection of ML, software engineering, and scalable infrastructure.\n\n\nTHE TEAM\n\nThe ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. The team works closely with research, data, and platform engineers to ensure models can scale from prototype to production-grade training runs.\n\n\nIN THIS ROLE YOU WILL\n\n- Own training/inference infrastructure: Design, implement, and maintain systems for large-scale model training, including scheduling, job management, checkpointing, and metrics/logging.\n\n- Scale distributed training: Work with researchers to scale JAX-based training across TPU and GPU clusters with minimal friction.\n\n- Optimize performance: Profile and improve memory usage, device utilization, throughput, and distributed synchronization.\n\n- Enable rapid iteration: Build abstractions for launching, monitoring, debugging, and reproducing experiments.\n\n- Manage compute resources: Ensure efficient allocation and utilization of cloud-based GPU/TPU compute while controlling cost.\n\n- Partner with researchers: Translate research needs into infra capabilities and guide best practices for training at scale.\n\n- Contribute to core training code: Evolve JAX model and training code to support new architectures, modalities, and evaluation metrics.\n\n\nWHAT WE HOPE YOU’LL BRING\n\n- Strong software engineering fundamentals and experience building ML training infrastructure or internal platforms.\n\n- Hands-on large-scale training experience in JAX (preferred), PyTorch.\n\n- Familiarity with distributed training, multi-host setups, data loaders, and evaluation pipelines.\n\n- Experience managing training workloads on cloud platforms (e.g., SLURM, Kubernetes, GCP TPU/GKE, AWS).\n\n- Ability to debug and optimize performance bottlenecks across the training stack.\n\n- Strong cross-functional communication and ownership mindset.\n\n\nBONUS POINTS IF YOU HAVE\n\n- Deep ML systems background (e.g., training compilers, runtime optimization, custom kernels).\n\n- Experience operating close to hardware (GPU/TPU performance tuning).\n\n- Background in robotics, multimodal models, or large-scale foundation models.\n\n- Experience designing abstractions that balance researcher flexibility with system reliability."},{"id":"52fb2d63-f18e-446e-8a15-cbcdc8740147","title":"Robot Build Technician","department":"Hardware","team":"Hardware","employmentType":"FullTime","location":"Fremont","secondaryLocations":[],"publishedAt":"2026-02-16T05:36:46.676+00:00","isListed":true,"isRemote":null,"workplaceType":null,"address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"Fremont"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/52fb2d63-f18e-446e-8a15-cbcdc8740147","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/52fb2d63-f18e-446e-8a15-cbcdc8740147/application","descriptionHtml":"<p style=\"min-height:1.5em\">We're looking for a hands-on <strong>Build Technician</strong> who thrives in a fast-paced hardware environment. You'll be responsible for building, assembling, and maintaining the robotic systems that power our data collection and model training operations.</p><p style=\"min-height:1.5em\">You'll work directly with our Hardware Engineering team to bring robots from prototype to production, ensuring quality and reliability at every step.</p><p style=\"min-height:1.5em\"><strong>What You'll Do</strong>:</p><p style=\"min-height:1.5em\">- Build and assemble robotic systems according to engineering specifications, including mechanical, electrical, and electromechanical components</p><p style=\"min-height:1.5em\">- Install, calibrate, and configure robots and end-of-arm tooling for various applications</p><p style=\"min-height:1.5em\">- Execute test protocols and quality checks to ensure robots function as designed</p><p style=\"min-height:1.5em\">- Maintain detailed service records and documentation for robotic equipment</p><p style=\"min-height:1.5em\">- Support hardware bring-up, including wiring, harnessing, and integration of sensors and actuators</p><p style=\"min-height:1.5em\">- Collaborate with mechanical, electrical, and software engineers to root-cause manufacturing issues and implement solutions</p><p style=\"min-height:1.5em\">- Manage inventory of parts, tools, and consumables for the hardware lab</p><p style=\"min-height:1.5em\">- Train team members on assembly procedures and best practices</p><p style=\"min-height:1.5em\"><strong>Competencies and Skills</strong>:</p><p style=\"min-height:1.5em\">- 2+ years of experience in mechanical or electromechanical assembly, robotics, or manufacturing environments</p><p style=\"min-height:1.5em\">- Proficiency with hand tools, power tools, and lab equipment (soldering, crimping, torque wrenches)</p><p style=\"min-height:1.5em\">- Experience with cable harnessing, wire routing, and electrical integration</p><p style=\"min-height:1.5em\">- Ability to read and interpret mechanical drawings, schematics, and assembly instructions</p><p style=\"min-height:1.5em\">- Familiarity with robotic systems, PLCs, or automated equipment is a plus</p><p style=\"min-height:1.5em\">- Basic understanding of CAN bus, Ethernet, and communication protocols</p><p style=\"min-height:1.5em\">- Strong troubleshooting skills and attention to detail</p><p style=\"min-height:1.5em\">- Comfortable working in a fast-paced, iterative environment</p><p style=\"min-height:1.5em\">- Experience with inventory management and documentation tools (Notion, Excel)</p><p style=\"min-height:1.5em\">- Prior experience in robotics, automotive, aerospace, or consumer electronics is highly valued</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"We're looking for a hands-on Build Technician who thrives in a fast-paced hardware environment. You'll be responsible for building, assembling, and maintaining the robotic systems that power our data collection and model training operations.\n\nYou'll work directly with our Hardware Engineering team to bring robots from prototype to production, ensuring quality and reliability at every step.\n\nWhat You'll Do:\n\n- Build and assemble robotic systems according to engineering specifications, including mechanical, electrical, and electromechanical components\n\n- Install, calibrate, and configure robots and end-of-arm tooling for various applications\n\n- Execute test protocols and quality checks to ensure robots function as designed\n\n- Maintain detailed service records and documentation for robotic equipment\n\n- Support hardware bring-up, including wiring, harnessing, and integration of sensors and actuators\n\n- Collaborate with mechanical, electrical, and software engineers to root-cause manufacturing issues and implement solutions\n\n- Manage inventory of parts, tools, and consumables for the hardware lab\n\n- Train team members on assembly procedures and best practices\n\nCompetencies and Skills:\n\n- 2+ years of experience in mechanical or electromechanical assembly, robotics, or manufacturing environments\n\n- Proficiency with hand tools, power tools, and lab equipment (soldering, crimping, torque wrenches)\n\n- Experience with cable harnessing, wire routing, and electrical integration\n\n- Ability to read and interpret mechanical drawings, schematics, and assembly instructions\n\n- Familiarity with robotic systems, PLCs, or automated equipment is a plus\n\n- Basic understanding of CAN bus, Ethernet, and communication protocols\n\n- Strong troubleshooting skills and attention to detail\n\n- Comfortable working in a fast-paced, iterative environment\n\n- Experience with inventory management and documentation tools (Notion, Excel)\n\n- Prior experience in robotics, automotive, aerospace, or consumer electronics is highly valued\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"58e5a454-47db-41b2-9c5d-c8e34c55159e","title":"Mechanical Design Engineer","department":"Hardware","team":"Hardware","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2025-06-14T01:31:23.758+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/58e5a454-47db-41b2-9c5d-c8e34c55159e","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/58e5a454-47db-41b2-9c5d-c8e34c55159e/application","descriptionHtml":"<p style=\"min-height:1.5em\">We're looking for an experienced mechanical engineer to drive the integration and development of our robotic systems, leading innovative designs from concept to deployment. You'll own the full spectrum of mechanical development—from actuator sizing or design to kinematics and work with teams to prototype and ultimately produce systems at scale—ensuring reliability, deployability, and performance. The ideal candidate is a hands-on innovator with deep expertise in mechatronic systems, combining theoretical knowledge with practical engineering skills. Experience with actuation systems, electromechanical integration, machine design, and a track record of bringing mechanical systems to life is essential. If this sounds like you, please apply!</p><h2><br />In This Role You Will</h2><p style=\"min-height:1.5em\"><strong>- Own the mechanical design lifecycle:</strong> Drive all design decisions around 3D CAD, 2D drawings, material selection, and manufacturability — from early concept and proof-of-concept prototypes through high-volume production.</p><p style=\"min-height:1.5em\"><strong>- Develop and refine manufacturing processes:</strong> Identify and optimize injection molding, die casting, stamping, machining, adhesives, and bonding methods for new and existing products.</p><p style=\"min-height:1.5em\"><strong>- Ensure reliability and robustness:</strong> Perform and interpret reliability tests (HALT/HASS, tolerance stack-ups, environmental testing) and lead corrective design actions.</p><p style=\"min-height:1.5em\"><strong>- Leverage simulation for smart decisions:</strong> Use basic FEA tools (thermal, structural, vibrational) and first-order analyses to validate or guide design from early phases onward.</p><p style=\"min-height:1.5em\"><strong>- Lead system integration efforts:</strong> Collaborate with electrical and radio teams to balance thermal, EMI, mechanical stability, and accessibility needs in tightly integrated assemblies.</p><p style=\"min-height:1.5em\"><strong>- Prototype and iterate quickly:</strong> Build proof-of-concept designs, run experiments, and translate findings into high-yield, mass-production-ready solutions.</p><p style=\"min-height:1.5em\"><strong>- Manage vendor relationships:</strong> Evaluate DFM, cost, yield, and timeline trade-offs; work with JDM/CM/ODM partners; own and drive supplier selection where needed.</p><p style=\"min-height:1.5em\"><strong>- Communicate effectively across teams:</strong> Conduct design reviews with cross-functional stakeholders, clearly articulating design rationale, risks, and trade-offs.</p><p style=\"min-height:1.5em\"></p><h2><strong>What We Hope You'll Bring</strong></h2><p style=\"min-height:1.5em\">- 7+ years of experience taking hardware products from concept to production, with a strong portfolio of shipped mechanical designs — preferably in robotics, automotive, or consumer products</p><p style=\"min-height:1.5em\">- Bachelor's Degree in Mechanical or Aerospace Engineering, or equivalent experience</p><p style=\"min-height:1.5em\">- Deep understanding of high-volume manufacturing processes (injection molding, die casting, stamping, machining, bonding)</p><p style=\"min-height:1.5em\">- Familiarity with HALT/HASS, FMEA, DOE methodologies, and test-to-failure approaches for robust mechanical design</p><p style=\"min-height:1.5em\">- Practical understanding of when and how to apply FEA tools, with the ability to make first-order engineering judgments</p><p style=\"min-height:1.5em\">- Proven record of mechanically integrating electronics (sensors, PCBs, antennas, batteries) in complex assemblies</p><p style=\"min-height:1.5em\">- Ability to lead reviews, influence cross-functional teams, and convey risks and solutions clearly</p><p style=\"min-height:1.5em\">- Comfort in early-stage, resource-limited startup environments with a willingness to move quickly and hands-on</p><p style=\"min-height:1.5em\">- Proficiency in prototyping methods including machining (mill, lathe), sheet metal fabrication, 3D printing, and injection molding</p><p style=\"min-height:1.5em\">- Experience building and testing prototypes and analyzing failures to implement improvements</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"We're looking for an experienced mechanical engineer to drive the integration and development of our robotic systems, leading innovative designs from concept to deployment. You'll own the full spectrum of mechanical development—from actuator sizing or design to kinematics and work with teams to prototype and ultimately produce systems at scale—ensuring reliability, deployability, and performance. The ideal candidate is a hands-on innovator with deep expertise in mechatronic systems, combining theoretical knowledge with practical engineering skills. Experience with actuation systems, electromechanical integration, machine design, and a track record of bringing mechanical systems to life is essential. If this sounds like you, please apply!\n\n\n\nIN THIS ROLE YOU WILL\n\n- Own the mechanical design lifecycle: Drive all design decisions around 3D CAD, 2D drawings, material selection, and manufacturability — from early concept and proof-of-concept prototypes through high-volume production.\n\n- Develop and refine manufacturing processes: Identify and optimize injection molding, die casting, stamping, machining, adhesives, and bonding methods for new and existing products.\n\n- Ensure reliability and robustness: Perform and interpret reliability tests (HALT/HASS, tolerance stack-ups, environmental testing) and lead corrective design actions.\n\n- Leverage simulation for smart decisions: Use basic FEA tools (thermal, structural, vibrational) and first-order analyses to validate or guide design from early phases onward.\n\n- Lead system integration efforts: Collaborate with electrical and radio teams to balance thermal, EMI, mechanical stability, and accessibility needs in tightly integrated assemblies.\n\n- Prototype and iterate quickly: Build proof-of-concept designs, run experiments, and translate findings into high-yield, mass-production-ready solutions.\n\n- Manage vendor relationships: Evaluate DFM, cost, yield, and timeline trade-offs; work with JDM/CM/ODM partners; own and drive supplier selection where needed.\n\n- Communicate effectively across teams: Conduct design reviews with cross-functional stakeholders, clearly articulating design rationale, risks, and trade-offs.\n\n\nWHAT WE HOPE YOU'LL BRING\n\n- 7+ years of experience taking hardware products from concept to production, with a strong portfolio of shipped mechanical designs — preferably in robotics, automotive, or consumer products\n\n- Bachelor's Degree in Mechanical or Aerospace Engineering, or equivalent experience\n\n- Deep understanding of high-volume manufacturing processes (injection molding, die casting, stamping, machining, bonding)\n\n- Familiarity with HALT/HASS, FMEA, DOE methodologies, and test-to-failure approaches for robust mechanical design\n\n- Practical understanding of when and how to apply FEA tools, with the ability to make first-order engineering judgments\n\n- Proven record of mechanically integrating electronics (sensors, PCBs, antennas, batteries) in complex assemblies\n\n- Ability to lead reviews, influence cross-functional teams, and convey risks and solutions clearly\n\n- Comfort in early-stage, resource-limited startup environments with a willingness to move quickly and hands-on\n\n- Proficiency in prototyping methods including machining (mill, lathe), sheet metal fabrication, 3D printing, and injection molding\n\n- Experience building and testing prototypes and analyzing failures to implement improvements\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"0307dd1e-ac14-47fd-b80c-e3ca6e82ae46","title":"ML Infra Engineer (Supercomputing)","department":"Machine Learning","team":"Machine Learning","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-03-07T02:53:28.760+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/0307dd1e-ac14-47fd-b80c-e3ca6e82ae46","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/0307dd1e-ac14-47fd-b80c-e3ca6e82ae46/application","descriptionHtml":"<p style=\"min-height:1.5em\">Physical Intelligence builds general-purpose AI for the physical world. Training our models requires orchestrating thousands of accelerators across a heterogeneous fleet of GPU and TPU clusters — spanning different hardware generations, cloud providers, and cluster topologies.</p><p style=\"min-height:1.5em\">Today, researchers often need to know which cluster to target, what resources are available, and how to configure their jobs accordingly. That doesn't scale. We need a scheduling and compute layer that makes the right placement decision automatically — routing jobs to the best cluster based on availability, hardware fit, cost, and priority — so researchers can focus entirely on the science.</p><p style=\"min-height:1.5em\">This role owns that problem end-to-end: the scheduling systems, the placement logic, the cluster management layer, and the operational tooling that keeps it all running.</p><p style=\"min-height:1.5em\">This is not cloud DevOps. It's not about standing up clusters and walking away. It's a <strong>systems role</strong> for people who care about intelligent resource allocation, utilization, fault tolerance, and making large-scale distributed training seamless.</p><p style=\"min-height:1.5em\"></p><h2>The Team</h2><p style=\"min-height:1.5em\">The ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. You will work closely with ML Infra (training systems), data platform, and research teams to ensure compute scheduling is never the bottleneck.</p><p style=\"min-height:1.5em\"></p><h2>In This Role You Will</h2><p style=\"min-height:1.5em\"><strong>- Own Intelligent Job Scheduling and Placement</strong>: Design and build multi-tenant scheduling systems that automatically place training jobs on the best available cluster based on hardware requirements, topology, availability, cost, and priority. Support fair resource sharing across teams and projects with quota management, priority tiers, and preemption policies. Abstract away cluster differences so researchers submit jobs without needing to know where they will land.</p><p style=\"min-height:1.5em\"><strong>- Scale Multi-cluster Orchestration</strong>: Build the control plane that manages the job lifecycle across diverse clusters (mixed GPU/TPU, multi-generation hardware, on-prem/cloud) and enables seamless job migration, failover, and re-scheduling.</p><p style=\"min-height:1.5em\"><strong>- Optimize Accelerator Utilization and Efficiency</strong>: Monitor and optimize GPU/TPU utilization across the entire fleet. Implement priority, preemption, queueing, and fairness policies that balance research velocity with cost efficiency.</p><p style=\"min-height:1.5em\"><strong>- Ensure Scaling and Stability</strong>: Implement fault detection, automatic recovery, and resilience for long-running multi-node training jobs. Manage health checking, node management, and scaling to thousands of accelerators.</p><p style=\"min-height:1.5em\"><strong>- Support Inference and Robot Deployment</strong>: Extend scheduling and orchestration to inference workloads, including deploying models to edge devices on physical robots.</p><p style=\"min-height:1.5em\"><strong>- Enhance Observability and Developer Experience</strong>: Build the dashboards, alerting, SLOs, and debugging tools necessary for researchers to understand job status and for the team to ensure high scheduling quality and cluster reliability.</p><p style=\"min-height:1.5em\"></p><h1>What We Hope You’ll Bring</h1><p style=\"min-height:1.5em\">We’re intentionally flexible on exact background, but strong candidates usually have:</p><p style=\"min-height:1.5em\">- Strong software engineering fundamentals</p><p style=\"min-height:1.5em\"><strong>- Experience building or operating job scheduling / resource management systems at scale</strong></p><p style=\"min-height:1.5em\"><strong>- Experience with large-scale compute clusters (GPU and/or TPU)</strong></p><p style=\"min-height:1.5em\">- Familiarity with schedulers and orchestration systems (SLURM, Kubernetes, GKE, K3S, or internal equivalents)</p><p style=\"min-height:1.5em\">- Comfort reasoning about resource allocation, bin-packing, priority scheduling, and multi-tenancy</p><p style=\"min-height:1.5em\">- Understanding of how ML training workloads behave — long-running, multi-node, sensitive to stragglers, topology-dependent</p><p style=\"min-height:1.5em\">- A bias toward owning systems end-to-end, from design to operation</p><p style=\"min-height:1.5em\">- Enjoy working closely with researchers and unblocking fast-moving projects</p><p style=\"min-height:1.5em\"></p><h1>Bonus Points If You Have</h1><p style=\"min-height:1.5em\">- Experience building multi-cluster or federated scheduling systems</p><p style=\"min-height:1.5em\">- Experience with TPU infrastructure (GCP TPU slices, Multislice, GKE)</p><p style=\"min-height:1.5em\">- Background in cluster resource managers (Borg, YARN, Mesos, or custom schedulers)</p><p style=\"min-height:1.5em\">- Linux systems engineering, networking, and infrastructure-as-code</p><p style=\"min-height:1.5em\">- NCCL/collective communication and topology-aware placement</p><p style=\"min-height:1.5em\">- Experience with capacity planning and cloud cost optimization at scale</p><p style=\"min-height:1.5em\">- Familiarity with JAX, PyTorch, or similar ML frameworks at the runtime/systems level</p><p style=\"min-height:1.5em\">In this role you will help scale and optimize our training systems and core model code. You’ll own critical infrastructure for large-scale training, from managing GPU/TPU compute and job orchestration to building reusable and efficient JAX training pipelines. You’ll work closely with researchers and model engineers to translate ideas into experiments—and those experiments into production training runs.</p><p style=\"min-height:1.5em\">This is a hands-on, high-leverage role at the intersection of ML, software engineering, and scalable infrastructure.</p><p style=\"min-height:1.5em\"><strong>The Team</strong></p><p style=\"min-height:1.5em\">The ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. The team works closely with research, data, and platform engineers to ensure models can scale from prototype to production-grade training runs.</p><p style=\"min-height:1.5em\"><strong>In This Role You Will</strong></p><p style=\"min-height:1.5em\"><strong>- Own training/inference infrastructure:</strong> Design, implement, and maintain systems for large-scale model training, including scheduling, job management, checkpointing, and metrics/logging.</p><p style=\"min-height:1.5em\"><strong>- Scale distributed training:</strong> Work with researchers to scale JAX-based training across TPU and GPU clusters with minimal friction.</p><p style=\"min-height:1.5em\"><strong>- Optimize performance:</strong> Profile and improve memory usage, device utilization, throughput, and distributed synchronization.</p><p style=\"min-height:1.5em\"><strong>- Enable rapid iteration: </strong>Build abstractions for launching, monitoring, debugging, and reproducing experiments.</p><p style=\"min-height:1.5em\"><strong>- Manage compute resources:</strong> Ensure efficient allocation and utilization of cloud-based GPU/TPU compute while controlling cost.</p><p style=\"min-height:1.5em\"><strong>- Partner with researchers: </strong>Translate research needs into infra capabilities and guide best practices for training at scale.</p><p style=\"min-height:1.5em\"><strong>- Contribute to core training code:</strong> Evolve JAX model and training code to support new architectures, modalities, and evaluation metrics.</p><p style=\"min-height:1.5em\"><strong>What We Hope You’ll Bring</strong></p><p style=\"min-height:1.5em\">- Strong software engineering fundamentals and experience building ML training infrastructure or internal platforms.</p><p style=\"min-height:1.5em\">- Hands-on large-scale training experience in JAX (preferred), PyTorch.</p><p style=\"min-height:1.5em\">- Familiarity with distributed training, multi-host setups, data loaders, and evaluation pipelines.</p><p style=\"min-height:1.5em\">- Experience managing training workloads on cloud platforms (e.g., SLURM, Kubernetes, GCP TPU/GKE, AWS).</p><p style=\"min-height:1.5em\">- Ability to debug and optimize performance bottlenecks across the training stack.</p><p style=\"min-height:1.5em\">- Strong cross-functional communication and ownership mindset.</p><p style=\"min-height:1.5em\"><strong>Bonus Points If You Have</strong></p><p style=\"min-height:1.5em\">- Deep ML systems background (e.g., training compilers, runtime optimization, custom kernels).</p><p style=\"min-height:1.5em\">- Experience operating close to hardware (GPU/TPU performance tuning).</p><p style=\"min-height:1.5em\">- Background in robotics, multimodal models, or large-scale foundation models.</p><p style=\"min-height:1.5em\">- Experience designing abstractions that balance researcher flexibility with system reliability.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"Physical Intelligence builds general-purpose AI for the physical world. Training our models requires orchestrating thousands of accelerators across a heterogeneous fleet of GPU and TPU clusters — spanning different hardware generations, cloud providers, and cluster topologies.\n\nToday, researchers often need to know which cluster to target, what resources are available, and how to configure their jobs accordingly. That doesn't scale. We need a scheduling and compute layer that makes the right placement decision automatically — routing jobs to the best cluster based on availability, hardware fit, cost, and priority — so researchers can focus entirely on the science.\n\nThis role owns that problem end-to-end: the scheduling systems, the placement logic, the cluster management layer, and the operational tooling that keeps it all running.\n\nThis is not cloud DevOps. It's not about standing up clusters and walking away. It's a systems role for people who care about intelligent resource allocation, utilization, fault tolerance, and making large-scale distributed training seamless.\n\n\nTHE TEAM\n\nThe ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. You will work closely with ML Infra (training systems), data platform, and research teams to ensure compute scheduling is never the bottleneck.\n\n\nIN THIS ROLE YOU WILL\n\n- Own Intelligent Job Scheduling and Placement: Design and build multi-tenant scheduling systems that automatically place training jobs on the best available cluster based on hardware requirements, topology, availability, cost, and priority. Support fair resource sharing across teams and projects with quota management, priority tiers, and preemption policies. Abstract away cluster differences so researchers submit jobs without needing to know where they will land.\n\n- Scale Multi-cluster Orchestration: Build the control plane that manages the job lifecycle across diverse clusters (mixed GPU/TPU, multi-generation hardware, on-prem/cloud) and enables seamless job migration, failover, and re-scheduling.\n\n- Optimize Accelerator Utilization and Efficiency: Monitor and optimize GPU/TPU utilization across the entire fleet. Implement priority, preemption, queueing, and fairness policies that balance research velocity with cost efficiency.\n\n- Ensure Scaling and Stability: Implement fault detection, automatic recovery, and resilience for long-running multi-node training jobs. Manage health checking, node management, and scaling to thousands of accelerators.\n\n- Support Inference and Robot Deployment: Extend scheduling and orchestration to inference workloads, including deploying models to edge devices on physical robots.\n\n- Enhance Observability and Developer Experience: Build the dashboards, alerting, SLOs, and debugging tools necessary for researchers to understand job status and for the team to ensure high scheduling quality and cluster reliability.\n\n\nWHAT WE HOPE YOU’LL BRING\n\nWe’re intentionally flexible on exact background, but strong candidates usually have:\n\n- Strong software engineering fundamentals\n\n- Experience building or operating job scheduling / resource management systems at scale\n\n- Experience with large-scale compute clusters (GPU and/or TPU)\n\n- Familiarity with schedulers and orchestration systems (SLURM, Kubernetes, GKE, K3S, or internal equivalents)\n\n- Comfort reasoning about resource allocation, bin-packing, priority scheduling, and multi-tenancy\n\n- Understanding of how ML training workloads behave — long-running, multi-node, sensitive to stragglers, topology-dependent\n\n- A bias toward owning systems end-to-end, from design to operation\n\n- Enjoy working closely with researchers and unblocking fast-moving projects\n\n\nBONUS POINTS IF YOU HAVE\n\n- Experience building multi-cluster or federated scheduling systems\n\n- Experience with TPU infrastructure (GCP TPU slices, Multislice, GKE)\n\n- Background in cluster resource managers (Borg, YARN, Mesos, or custom schedulers)\n\n- Linux systems engineering, networking, and infrastructure-as-code\n\n- NCCL/collective communication and topology-aware placement\n\n- Experience with capacity planning and cloud cost optimization at scale\n\n- Familiarity with JAX, PyTorch, or similar ML frameworks at the runtime/systems level\n\nIn this role you will help scale and optimize our training systems and core model code. You’ll own critical infrastructure for large-scale training, from managing GPU/TPU compute and job orchestration to building reusable and efficient JAX training pipelines. You’ll work closely with researchers and model engineers to translate ideas into experiments—and those experiments into production training runs.\n\nThis is a hands-on, high-leverage role at the intersection of ML, software engineering, and scalable infrastructure.\n\nThe Team\n\nThe ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. The team works closely with research, data, and platform engineers to ensure models can scale from prototype to production-grade training runs.\n\nIn This Role You Will\n\n- Own training/inference infrastructure: Design, implement, and maintain systems for large-scale model training, including scheduling, job management, checkpointing, and metrics/logging.\n\n- Scale distributed training: Work with researchers to scale JAX-based training across TPU and GPU clusters with minimal friction.\n\n- Optimize performance: Profile and improve memory usage, device utilization, throughput, and distributed synchronization.\n\n- Enable rapid iteration: Build abstractions for launching, monitoring, debugging, and reproducing experiments.\n\n- Manage compute resources: Ensure efficient allocation and utilization of cloud-based GPU/TPU compute while controlling cost.\n\n- Partner with researchers: Translate research needs into infra capabilities and guide best practices for training at scale.\n\n- Contribute to core training code: Evolve JAX model and training code to support new architectures, modalities, and evaluation metrics.\n\nWhat We Hope You’ll Bring\n\n- Strong software engineering fundamentals and experience building ML training infrastructure or internal platforms.\n\n- Hands-on large-scale training experience in JAX (preferred), PyTorch.\n\n- Familiarity with distributed training, multi-host setups, data loaders, and evaluation pipelines.\n\n- Experience managing training workloads on cloud platforms (e.g., SLURM, Kubernetes, GCP TPU/GKE, AWS).\n\n- Ability to debug and optimize performance bottlenecks across the training stack.\n\n- Strong cross-functional communication and ownership mindset.\n\nBonus Points If You Have\n\n- Deep ML systems background (e.g., training compilers, runtime optimization, custom kernels).\n\n- Experience operating close to hardware (GPU/TPU performance tuning).\n\n- Background in robotics, multimodal models, or large-scale foundation models.\n\n- Experience designing abstractions that balance researcher flexibility with system reliability.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"c245f446-c371-44fb-a0a4-0735318abe7b","title":"Instruction Writing Lead","department":"Operations","team":"Operations","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-04-08T16:25:04.639+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/c245f446-c371-44fb-a0a4-0735318abe7b","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/c245f446-c371-44fb-a0a4-0735318abe7b/application","descriptionHtml":"<p style=\"min-height:1.5em\"><strong>Who we are</strong></p><p style=\"min-height:1.5em\">Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.</p><p style=\"min-height:1.5em\"><strong>The team</strong></p><p style=\"min-height:1.5em\"><em>Within Ops, there are three functions: Prototyping, Process Engineering, and Production Ops. <u>This role will sit in Prototyping — the starting point of the pipeline, where research intent gets translated into executable plans before anything moves downstream.</u></em></p><p style=\"min-height:1.5em\"><strong>In this role you will:</strong></p><p style=\"min-height:1.5em\">-Own validation of instructions before release to Production Ops, ensuring accuracy, completeness, and execution readiness</p><p style=\"min-height:1.5em\">-Translate prototyping outputs into structured, production-ready instructions with consistent logic and formatting</p><p style=\"min-height:1.5em\">-Determine the best method for instruction delivery to end users</p><p style=\"min-height:1.5em\">-Work with international team to ensure delivery is appropriate for their team – alternative language instructions, videos, etc.</p><p style=\"min-height:1.5em\">-Define and maintain instruction templates in partnership with Process Engineering</p><p style=\"min-height:1.5em\">-Manage and support the onsite instruction-writing team, including review workflows and prioritization</p><p style=\"min-height:1.5em\">-Establish scalable documentation processes across data collection, evaluation, scorecard, and QA instruction sets</p><p style=\"min-height:1.5em\">-Partner with Prototyping to improve handoff quality and reduce downstream rework</p><p style=\"min-height:1.5em\">-Represent instruction-writing requirements in tooling, template design, and release standards</p><p style=\"min-height:1.5em\">-Define and track instruction quality and coverage metrics as output scales</p><p style=\"min-height:1.5em\">-Support international rollout by ensuring instructions are localization-ready, regionally adaptable, and usable across distributed Production Ops teams</p><p style=\"min-height:1.5em\"><strong><br /></strong><em>Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</em></p>","descriptionPlain":"Who we are\n\nPhysical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.\n\nThe team\n\nWithin Ops, there are three functions: Prototyping, Process Engineering, and Production Ops. This role will sit in Prototyping — the starting point of the pipeline, where research intent gets translated into executable plans before anything moves downstream.\n\nIn this role you will:\n\n-Own validation of instructions before release to Production Ops, ensuring accuracy, completeness, and execution readiness\n\n-Translate prototyping outputs into structured, production-ready instructions with consistent logic and formatting\n\n-Determine the best method for instruction delivery to end users\n\n-Work with international team to ensure delivery is appropriate for their team – alternative language instructions, videos, etc.\n\n-Define and maintain instruction templates in partnership with Process Engineering\n\n-Manage and support the onsite instruction-writing team, including review workflows and prioritization\n\n-Establish scalable documentation processes across data collection, evaluation, scorecard, and QA instruction sets\n\n-Partner with Prototyping to improve handoff quality and reduce downstream rework\n\n-Represent instruction-writing requirements in tooling, template design, and release standards\n\n-Define and track instruction quality and coverage metrics as output scales\n\n-Support international rollout by ensuring instructions are localization-ready, regionally adaptable, and usable across distributed Production Ops teams\n\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"70ebf855-16df-4879-a6a7-ee0161174acc","title":"ML Infra Engineer","department":"Machine Learning","team":"Machine Learning","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2024-08-24T23:19:50.252+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/70ebf855-16df-4879-a6a7-ee0161174acc","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/70ebf855-16df-4879-a6a7-ee0161174acc/application","descriptionHtml":"<p style=\"min-height:1.5em\">In this role you will help scale and optimize our training systems and core model code. You’ll own critical infrastructure for large-scale training, from managing GPU/TPU compute and job orchestration to building reusable and efficient JAX training pipelines. You’ll work closely with researchers and model engineers to translate ideas into experiments—and those experiments into production training runs.</p><p style=\"min-height:1.5em\">This is a hands-on, high-leverage role at the intersection of ML, software engineering, and scalable infrastructure.</p><p style=\"min-height:1.5em\"><strong>The Team</strong></p><p style=\"min-height:1.5em\">The ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. The team works closely with research, data, and platform engineers to ensure models can scale from prototype to production-grade training runs.</p><p style=\"min-height:1.5em\"><strong>In This Role You Will</strong></p><p style=\"min-height:1.5em\"><strong>- Own training/inference infrastructure:</strong> Design, implement, and maintain systems for large-scale model training, including scheduling, job management, checkpointing, and metrics/logging.</p><p style=\"min-height:1.5em\"><strong>- Scale distributed training:</strong> Work with researchers to scale JAX-based training across TPU and GPU clusters with minimal friction.</p><p style=\"min-height:1.5em\"><strong>- Optimize performance:</strong> Profile and improve memory usage, device utilization, throughput, and distributed synchronization.</p><p style=\"min-height:1.5em\"><strong>- Enable rapid iteration: </strong>Build abstractions for launching, monitoring, debugging, and reproducing experiments.</p><p style=\"min-height:1.5em\"><strong>- Manage compute resources:</strong> Ensure efficient allocation and utilization of cloud-based GPU/TPU compute while controlling cost.</p><p style=\"min-height:1.5em\"><strong>- Partner with researchers: </strong>Translate research needs into infra capabilities and guide best practices for training at scale.</p><p style=\"min-height:1.5em\"><strong>- Contribute to core training code:</strong> Evolve JAX model and training code to support new architectures, modalities, and evaluation metrics.</p><p style=\"min-height:1.5em\"><strong>What We Hope You’ll Bring</strong></p><p style=\"min-height:1.5em\">- Strong software engineering fundamentals and experience building ML training infrastructure or internal platforms.</p><p style=\"min-height:1.5em\">- Hands-on large-scale training experience in JAX (preferred), PyTorch.</p><p style=\"min-height:1.5em\">- Familiarity with distributed training, multi-host setups, data loaders, and evaluation pipelines.</p><p style=\"min-height:1.5em\">- Experience managing training workloads on cloud platforms (e.g., SLURM, Kubernetes, GCP TPU/GKE, AWS).</p><p style=\"min-height:1.5em\">- Ability to debug and optimize performance bottlenecks across the training stack.</p><p style=\"min-height:1.5em\">- Strong cross-functional communication and ownership mindset.</p><p style=\"min-height:1.5em\"><strong>Bonus Points If You Have</strong></p><p style=\"min-height:1.5em\">- Deep ML systems background (e.g., training compilers, runtime optimization, custom kernels).</p><p style=\"min-height:1.5em\">- Experience operating close to hardware (GPU/TPU performance tuning).</p><p style=\"min-height:1.5em\">- Background in robotics, multimodal models, or large-scale foundation models.</p><p style=\"min-height:1.5em\">- Experience designing abstractions that balance researcher flexibility with system reliability.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"In this role you will help scale and optimize our training systems and core model code. You’ll own critical infrastructure for large-scale training, from managing GPU/TPU compute and job orchestration to building reusable and efficient JAX training pipelines. You’ll work closely with researchers and model engineers to translate ideas into experiments—and those experiments into production training runs.\n\nThis is a hands-on, high-leverage role at the intersection of ML, software engineering, and scalable infrastructure.\n\nThe Team\n\nThe ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. The team works closely with research, data, and platform engineers to ensure models can scale from prototype to production-grade training runs.\n\nIn This Role You Will\n\n- Own training/inference infrastructure: Design, implement, and maintain systems for large-scale model training, including scheduling, job management, checkpointing, and metrics/logging.\n\n- Scale distributed training: Work with researchers to scale JAX-based training across TPU and GPU clusters with minimal friction.\n\n- Optimize performance: Profile and improve memory usage, device utilization, throughput, and distributed synchronization.\n\n- Enable rapid iteration: Build abstractions for launching, monitoring, debugging, and reproducing experiments.\n\n- Manage compute resources: Ensure efficient allocation and utilization of cloud-based GPU/TPU compute while controlling cost.\n\n- Partner with researchers: Translate research needs into infra capabilities and guide best practices for training at scale.\n\n- Contribute to core training code: Evolve JAX model and training code to support new architectures, modalities, and evaluation metrics.\n\nWhat We Hope You’ll Bring\n\n- Strong software engineering fundamentals and experience building ML training infrastructure or internal platforms.\n\n- Hands-on large-scale training experience in JAX (preferred), PyTorch.\n\n- Familiarity with distributed training, multi-host setups, data loaders, and evaluation pipelines.\n\n- Experience managing training workloads on cloud platforms (e.g., SLURM, Kubernetes, GCP TPU/GKE, AWS).\n\n- Ability to debug and optimize performance bottlenecks across the training stack.\n\n- Strong cross-functional communication and ownership mindset.\n\nBonus Points If You Have\n\n- Deep ML systems background (e.g., training compilers, runtime optimization, custom kernels).\n\n- Experience operating close to hardware (GPU/TPU performance tuning).\n\n- Background in robotics, multimodal models, or large-scale foundation models.\n\n- Experience designing abstractions that balance researcher flexibility with system reliability.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"f83ba447-2261-4832-95db-a2f88454e0ba","title":"Research Scientist","department":"AI & Robotics Research","team":"AI & Robotics Research","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2024-08-24T23:22:49.675+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/f83ba447-2261-4832-95db-a2f88454e0ba","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/f83ba447-2261-4832-95db-a2f88454e0ba/application","descriptionHtml":"<p style=\"min-height:1.5em\">We are looking for researchers with a record of excellent research results in the fields of machine learning and robotics, at all levels. Successful candidates will have both excellent fundamentals and excellent implementation skills, with a record of both system-building and fundamental conceptual, algorithmic, or theoretical advances. We welcome applications from both academic researchers and researchers with unconventional backgrounds.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"We are looking for researchers with a record of excellent research results in the fields of machine learning and robotics, at all levels. Successful candidates will have both excellent fundamentals and excellent implementation skills, with a record of both system-building and fundamental conceptual, algorithmic, or theoretical advances. We welcome applications from both academic researchers and researchers with unconventional backgrounds.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"41dfbfcd-a9d1-4969-b11b-821f3319cae2","title":"Robot Prototype Technician","department":"Hardware","team":"Hardware","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-04-07T19:08:24.907+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/41dfbfcd-a9d1-4969-b11b-821f3319cae2","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/41dfbfcd-a9d1-4969-b11b-821f3319cae2/application","descriptionHtml":"<p style=\"min-height:1.5em\"><strong>Who We Are</strong></p><p style=\"min-height:1.5em\">Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.</p><p style=\"min-height:1.5em\"><strong>The Team</strong></p><p style=\"min-height:1.5em\">Robot Prototype Engineering Technicians collaborate closely with robot design engineers to build, test, and refine early stage robots. In this role you will use skills with assembly, fabrication, electronics, and troubleshooting to build initial robot designs, identify design flaws for improvement in future design iterations, propose solutions for improvements regarding build, maintenance, and repair of robots. These technicians are part of the robot fleet team within the PI Hardware Organization.</p><p style=\"min-height:1.5em\"><strong>In This Role You Will:</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\"><strong>Fabricate and Assembly Robot Prototype Systems and Components:</strong> Build mechanical/electrical prototypes using tools, 3D printing, soldering, and machining. Review and understand mechanical drawings, electrical schematics, and wiring diagrams for prototype assembly.</p></li><li><p style=\"min-height:1.5em\"><strong>Repair Robot Prototype Systems and Components:</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Repair mechanical components such as actuators, motors, gearboxes, bearings, and moving parts that could fail or break in initial prototype designs.</p></li><li><p style=\"min-height:1.5em\">Repair electrical systems including wiring, circuits, power supplies, sensors, and control systems that could fail or break in initial prototype designs.</p></li></ul></li><li><p style=\"min-height:1.5em\"><strong>Perform Basic Troubleshooting and Testing of Robot Prototype Systems and Components:</strong> Conduct basic functional tests and troubleshooting failures to engineering feedback to improve prototype designs. Perform tests on electrical systems using diagnostic tools, multimeters, oscilloscopes, and other specialized equipment.</p></li><li><p style=\"min-height:1.5em\"><strong>Collaboration Effectively with Hardware Design Engineers:</strong> Work with engineering teams to iterate designs based on experimental results. Propose solutions to hardware design engineering team for ease of assembly, repair, and maintenance</p></li></ul><p style=\"min-height:1.5em\"><strong>What We Hope You'll Bring</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">2+ years of prototyping technician experience</p></li><li><p style=\"min-height:1.5em\">Assembly and disassembly skills on electromechanical systems - Proficiency with electrical systems/components (AC/DC motors, wiring, controllers) and mechanical systems/components (motors, gears, Bearings).</p></li><li><p style=\"min-height:1.5em\">Soldering skills and harness/wiring skills</p></li><li><p style=\"min-height:1.5em\">Proficiency in using CAD software to view design files (e.g., Solidworks, Onshape) and ability to interpret engineering drawings and wiring diagrams</p></li><li><p style=\"min-height:1.5em\">Experience working with diagnostic tools, multimeters, oscilloscopes, and PLCs.</p></li><li><p style=\"min-height:1.5em\">Strong problem-solving ability</p></li><li><p style=\"min-height:1.5em\">Strong attention to detail</p></li><li><p style=\"min-height:1.5em\">Excellent communication and teamwork abilities</p></li></ul><p style=\"min-height:1.5em\"><strong>Bonus Points</strong></p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Proficiency with rapid prototyping tools and 3D printers</p></li><li><p style=\"min-height:1.5em\">Experience with robotic systems</p></li><li><p style=\"min-height:1.5em\">Associate degree in Electrical/Mechanical Engineering, Robotics, or a related technical field. A bachelor’s degree is a plus.</p></li><li><p style=\"min-height:1.5em\">Relevant certifications in electrical or mechanical systems (e.g., ASE, NATE, etc.)</p></li></ul>","descriptionPlain":"Who We Are\n\nPhysical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.\n\nThe Team\n\nRobot Prototype Engineering Technicians collaborate closely with robot design engineers to build, test, and refine early stage robots. In this role you will use skills with assembly, fabrication, electronics, and troubleshooting to build initial robot designs, identify design flaws for improvement in future design iterations, propose solutions for improvements regarding build, maintenance, and repair of robots. These technicians are part of the robot fleet team within the PI Hardware Organization.\n\nIn This Role You Will:\n\n - Fabricate and Assembly Robot Prototype Systems and Components: Build mechanical/electrical prototypes using tools, 3D printing, soldering, and machining. Review and understand mechanical drawings, electrical schematics, and wiring diagrams for prototype assembly.\n\n - Repair Robot Prototype Systems and Components:\n   \n   - Repair mechanical components such as actuators, motors, gearboxes, bearings, and moving parts that could fail or break in initial prototype designs.\n   \n   - Repair electrical systems including wiring, circuits, power supplies, sensors, and control systems that could fail or break in initial prototype designs.\n\n - Perform Basic Troubleshooting and Testing of Robot Prototype Systems and Components: Conduct basic functional tests and troubleshooting failures to engineering feedback to improve prototype designs. Perform tests on electrical systems using diagnostic tools, multimeters, oscilloscopes, and other specialized equipment.\n\n - Collaboration Effectively with Hardware Design Engineers: Work with engineering teams to iterate designs based on experimental results. Propose solutions to hardware design engineering team for ease of assembly, repair, and maintenance\n\nWhat We Hope You'll Bring\n\n - 2+ years of prototyping technician experience\n\n - Assembly and disassembly skills on electromechanical systems - Proficiency with electrical systems/components (AC/DC motors, wiring, controllers) and mechanical systems/components (motors, gears, Bearings).\n\n - Soldering skills and harness/wiring skills\n\n - Proficiency in using CAD software to view design files (e.g., Solidworks, Onshape) and ability to interpret engineering drawings and wiring diagrams\n\n - Experience working with diagnostic tools, multimeters, oscilloscopes, and PLCs.\n\n - Strong problem-solving ability\n\n - Strong attention to detail\n\n - Excellent communication and teamwork abilities\n\nBonus Points\n\n - Proficiency with rapid prototyping tools and 3D printers\n\n - Experience with robotic systems\n\n - Associate degree in Electrical/Mechanical Engineering, Robotics, or a related technical field. A bachelor’s degree is a plus.\n\n - Relevant certifications in electrical or mechanical systems (e.g., ASE, NATE, etc.)"},{"id":"e4301617-e5fb-413d-bc41-41a2d5e6b67e","title":"Robotics Research Engineer","department":"AI & Robotics Research","team":"AI & Robotics Research","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-04-13T22:21:55.043+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/e4301617-e5fb-413d-bc41-41a2d5e6b67e","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/e4301617-e5fb-413d-bc41-41a2d5e6b67e/application","descriptionHtml":"<h2><strong>Role Overview</strong></h2><p style=\"min-height:1.5em\">Physical Intelligence is bringing general-purpose AI into the physical world. We are a team of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.</p><p style=\"min-height:1.5em\">In this role, you will work at the intersection of hardware, software, and large-scale model training to develop effective autonomous robot policies. You’ll have the opportunity to work across the full stack behind state-of-the-art vision-language-action models: from designing robotic systems and data collection pipelines that produce high-quality training data, to developing learning algorithms that turn that data into capable, reliable policies. You’ll help shape the datasets, infrastructure, and research directions that define how these systems are built.</p><p style=\"min-height:1.5em\"></p><h2><strong>What You'll Do</strong></h2><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Build autonomous robot policies that operate robustly in the real world.</p></li><li><p style=\"min-height:1.5em\">Work across the full stack of robot learning, from hardware and data collection to training, evaluation, and deployment.</p></li><li><p style=\"min-height:1.5em\">Create new data collection methods and pipelines to generate the high-quality data that powers state-of-the-art robot models.</p></li><li><p style=\"min-height:1.5em\">Develop and refine vision-language-action models and learning algorithms for general-purpose manipulation and control.</p></li><li><p style=\"min-height:1.5em\">Curate and shape large-scale datasets, task distributions, and training recipes for robot pretraining and adaptation.</p></li><li><p style=\"min-height:1.5em\">Run fast, rigorous experiments to identify bottlenecks, uncover failure modes, and improve policy performance.</p></li><li><p style=\"min-height:1.5em\">Collaborate closely with researchers and engineers across robotics, infrastructure, and ML systems.</p></li><li><p style=\"min-height:1.5em\">Help define the technical roadmap for general-purpose physical intelligence.</p></li></ul><h2><strong>Competencies and Skills</strong></h2><p style=\"min-height:1.5em\">We are especially excited about candidates who combine strong robot learning intuition with deep practical engineering ability. Strong candidates will typically have many of the following:</p><ul style=\"min-height:1.5em\"><li><p style=\"min-height:1.5em\">Experience training machine learning models for robot control, ideally with policies that have been deployed and validated on real robots.</p></li><li><p style=\"min-height:1.5em\">Hands-on experience with the robotics full stack, including controls, robot runtime software, perception, state estimation, SLAM, and basic hardware bring-up and debugging.</p></li><li><p style=\"min-height:1.5em\">Strong software engineering and infrastructure skills, including building data pipelines, training systems, evaluation frameworks, and tools for rapid iteration.</p></li><li><p style=\"min-height:1.5em\">The ability to move seamlessly between research and implementation: designing experiments, training models, debugging failures, and improving system performance end to end.</p></li><li><p style=\"min-height:1.5em\">Comfort working hands on with robotic hardware.</p></li></ul><p style=\"min-height:1.5em\"><em>Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</em></p>","descriptionPlain":"ROLE OVERVIEW\n\nPhysical Intelligence is bringing general-purpose AI into the physical world. We are a team of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.\n\nIn this role, you will work at the intersection of hardware, software, and large-scale model training to develop effective autonomous robot policies. You’ll have the opportunity to work across the full stack behind state-of-the-art vision-language-action models: from designing robotic systems and data collection pipelines that produce high-quality training data, to developing learning algorithms that turn that data into capable, reliable policies. You’ll help shape the datasets, infrastructure, and research directions that define how these systems are built.\n\n\nWHAT YOU'LL DO\n\n - Build autonomous robot policies that operate robustly in the real world.\n\n - Work across the full stack of robot learning, from hardware and data collection to training, evaluation, and deployment.\n\n - Create new data collection methods and pipelines to generate the high-quality data that powers state-of-the-art robot models.\n\n - Develop and refine vision-language-action models and learning algorithms for general-purpose manipulation and control.\n\n - Curate and shape large-scale datasets, task distributions, and training recipes for robot pretraining and adaptation.\n\n - Run fast, rigorous experiments to identify bottlenecks, uncover failure modes, and improve policy performance.\n\n - Collaborate closely with researchers and engineers across robotics, infrastructure, and ML systems.\n\n - Help define the technical roadmap for general-purpose physical intelligence.\n\n\nCOMPETENCIES AND SKILLS\n\nWe are especially excited about candidates who combine strong robot learning intuition with deep practical engineering ability. Strong candidates will typically have many of the following:\n\n - Experience training machine learning models for robot control, ideally with policies that have been deployed and validated on real robots.\n\n - Hands-on experience with the robotics full stack, including controls, robot runtime software, perception, state estimation, SLAM, and basic hardware bring-up and debugging.\n\n - Strong software engineering and infrastructure skills, including building data pipelines, training systems, evaluation frameworks, and tools for rapid iteration.\n\n - The ability to move seamlessly between research and implementation: designing experiments, training models, debugging failures, and improving system performance end to end.\n\n - Comfort working hands on with robotic hardware.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"e501e135-9407-4b14-a8e8-c131f89be61d","title":"Shift Lead","department":"Operations","team":"Operations","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-04-16T16:56:34.399+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/e501e135-9407-4b14-a8e8-c131f89be61d","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/e501e135-9407-4b14-a8e8-c131f89be61d/application","descriptionHtml":"<p style=\"min-height:1.5em\"><strong>The Team</strong></p><p style=\"min-height:1.5em\">The Operations team drives the day-to-day execution of robot data collection and production at our San Francisco facility, partnering closely with research, hardware, and software teams to support our mission of bringing general-purpose AI into the physical world.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>In This Role You Will</strong></p><p style=\"min-height:1.5em\"><strong>- Onsite Floor Operations: </strong>Provide daily boots-on-the-ground leadership to drive data collection, verify availability of stations, props, and staffing, and ensure production continues smoothly during disruptions or staffing gaps. Lead and coordinate operators by assigning work and adjusting resources in real-time based on priorities and constraints.</p><p style=\"min-height:1.5em\"><strong>- Team Leadership &amp; People Development: </strong>Supervise, train, and develop operators, ensuring adherence to work standards. Provide ongoing coaching and feedback, treat operators fairly and professionally, and act as a liaison by bringing operator concerns to management’s attention.</p><p style=\"min-height:1.5em\"><strong>- Data Collection and Quality: </strong>Own factory throughput and data quality for your team; identify deviations from standard work, take immediate corrective action, and ensure all defects are properly documented and escalated.</p><p style=\"min-height:1.5em\"><strong>- Cross-Functional Communication &amp; Reporting: </strong>Act as the primary on-site point of contact for your team, maintaining a tight feedback loop between research, hardware, software, and floor operations. Proactively communicate status, technical blockers, hardware failures, and process bottlenecks. Maintain highly accurate shift handoff notes.</p><p style=\"min-height:1.5em\"><strong>- Safety &amp; Continuous Improvement: </strong>Enforce PPE compliance and safe work practices on the floor. Proactively identify, help resolve, and report unsafe conditions.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>What We Hope You’ll Bring</strong></p><p style=\"min-height:1.5em\">- Hold a bachelor’s degree in a STEM field, Operations, or similar or equivalent practical experience.</p><p style=\"min-height:1.5em\">-  3–5 years of experience in tech operations, manufacturing, or related fast-paced physical environments — ideally in robotics, autonomous vehicles, or other frontier hardware-AI integration sectors.</p><p style=\"min-height:1.5em\">- 2+ years of proven experience managing, scheduling, and motivating a team of hourly, shift-based workers.</p><p style=\"min-height:1.5em\">- Detail-oriented and comfortable using operational dashboards; ability to quickly learn proprietary robotics software interfaces.</p><p style=\"min-height:1.5em\">-  Clear, direct communicator who can translate operational gaps into structured feedback for technical teams; outstanding collaboration skills in cross-functional environments.</p><p style=\"min-height:1.5em\">- Excellent problem-solving abilities under pressure with a high bias for action and a demonstrated history of removing operational blockers in real-time.</p><p style=\"min-height:1.5em\">- Comfortable with ambiguity and changing priorities; able to manage multiple competing priorities with limited resources.</p><p style=\"min-height:1.5em\">- Adept at tracking KPIs and using metrics to inform operator performance management and workflow adjustments.</p><p style=\"min-height:1.5em\">- Safety-focused, detail-oriented, and quality-driven.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\"><strong>Bonus Points</strong></p><p style=\"min-height:1.5em\">- Experience in robotics or related fields.</p><p style=\"min-height:1.5em\"></p><p style=\"min-height:1.5em\">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</p>","descriptionPlain":"The Team\n\nThe Operations team drives the day-to-day execution of robot data collection and production at our San Francisco facility, partnering closely with research, hardware, and software teams to support our mission of bringing general-purpose AI into the physical world.\n\nIn This Role You Will\n\n- Onsite Floor Operations: Provide daily boots-on-the-ground leadership to drive data collection, verify availability of stations, props, and staffing, and ensure production continues smoothly during disruptions or staffing gaps. Lead and coordinate operators by assigning work and adjusting resources in real-time based on priorities and constraints.\n\n- Team Leadership & People Development: Supervise, train, and develop operators, ensuring adherence to work standards. Provide ongoing coaching and feedback, treat operators fairly and professionally, and act as a liaison by bringing operator concerns to management’s attention.\n\n- Data Collection and Quality: Own factory throughput and data quality for your team; identify deviations from standard work, take immediate corrective action, and ensure all defects are properly documented and escalated.\n\n- Cross-Functional Communication & Reporting: Act as the primary on-site point of contact for your team, maintaining a tight feedback loop between research, hardware, software, and floor operations. Proactively communicate status, technical blockers, hardware failures, and process bottlenecks. Maintain highly accurate shift handoff notes.\n\n- Safety & Continuous Improvement: Enforce PPE compliance and safe work practices on the floor. Proactively identify, help resolve, and report unsafe conditions.\n\nWhat We Hope You’ll Bring\n\n- Hold a bachelor’s degree in a STEM field, Operations, or similar or equivalent practical experience.\n\n- 3–5 years of experience in tech operations, manufacturing, or related fast-paced physical environments — ideally in robotics, autonomous vehicles, or other frontier hardware-AI integration sectors.\n\n- 2+ years of proven experience managing, scheduling, and motivating a team of hourly, shift-based workers.\n\n- Detail-oriented and comfortable using operational dashboards; ability to quickly learn proprietary robotics software interfaces.\n\n- Clear, direct communicator who can translate operational gaps into structured feedback for technical teams; outstanding collaboration skills in cross-functional environments.\n\n- Excellent problem-solving abilities under pressure with a high bias for action and a demonstrated history of removing operational blockers in real-time.\n\n- Comfortable with ambiguity and changing priorities; able to manage multiple competing priorities with limited resources.\n\n- Adept at tracking KPIs and using metrics to inform operator performance management and workflow adjustments.\n\n- Safety-focused, detail-oriented, and quality-driven.\n\nBonus Points\n\n- Experience in robotics or related fields.\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."},{"id":"eece24c0-3a0e-4373-bf88-4b92633a0930","title":"Electrical Engineer (UMI)","department":"Hardware","team":"Hardware","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-05-16T23:47:18.303+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/physicalintelligence/eece24c0-3a0e-4373-bf88-4b92633a0930","applyUrl":"https://jobs.ashbyhq.com/physicalintelligence/eece24c0-3a0e-4373-bf88-4b92633a0930/application","descriptionHtml":"<p style=\"min-height:1.5em\"><strong>Who we are</strong></p><p style=\"min-height:1.5em\">Physical Intelligence is bringing general-purpose AI into the physical world. We are a team of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.</p><p style=\"min-height:1.5em\"><strong>The team</strong></p><p style=\"min-height:1.5em\">This role is part of the hardware team, but will involve deep collaboration with the embedded firmware team and the robot software engineering (runtime) team.</p><p style=\"min-height:1.5em\"><strong>In this role you will:</strong></p><p style=\"min-height:1.5em\"><strong>- Drive Hardware Architecture:</strong> Lead the electrical design of devices crucial to PI’s data collection, from component selection (SoCs, Sensors, PMICs) to final PCBA.</p><p style=\"min-height:1.5em\"><strong>- Imaging System Design:</strong> Lead the hardware integration of high-resolution image sensors, ensuring clean power rails and high-speed data paths (MIPI) for optimal image quality.</p><p style=\"min-height:1.5em\"><strong>- Wireless Hardware Integration:</strong> Design and optimize RF front-ends for wireless modules, focusing on antenna placement, signal range, and power consumption.</p><p style=\"min-height:1.5em\"><strong>- Schematic &amp; Layout:</strong> Take full ownership of schematics and supervise/execute PCB layouts for complex, space-constrained enclosures.</p><p style=\"min-height:1.5em\"><strong>- Hardware Validation:</strong> Design and execute test plans to identify hardware bugs, signal integrity issues, and thermal bottlenecks.</p><p style=\"min-height:1.5em\"><strong> - DFM/DFT:</strong> Work with manufacturing partners to ensure designs are optimized for high-yield assembly (Design for Manufacturing) and comprehensive on-line testing (Design for Test).</p><p style=\"min-height:1.5em\"><strong>- Power Optimization:</strong> Analyze and optimize the hardware-level power consumption for battery-operated devices, and assist with thermal testing and validation of the devices.</p><p style=\"min-height:1.5em\"><strong>What we hope you'll bring:</strong></p><p style=\"min-height:1.5em\"><strong>Competencies and Skills</strong></p><p style=\"min-height:1.5em\">In addition to 3–7 years of experience in hardware design and board-level development for high-volume products, strong candidates must have:</p><p style=\"min-height:1.5em\"><strong>- BS/MS in Electrical Engineering</strong> or a related technical field.</p><p style=\"min-height:1.5em\"><strong>- PCB Design Expertise:</strong> Proficiency in EDA tools (e.g., Altium, Allegro) for complex, multi-layer, high-density interconnect designs, and experience with rigid flex circuits</p><p style=\"min-height:1.5em\"><strong>- Camera System Experience:</strong> Hands-on experience with CMOS image sensors, MIPI CSI-2/3 interfaces, and the electrical requirements for high-bandwidth imaging data, including bring-up and image tuning</p><p style=\"min-height:1.5em\"><strong>- High-Speed Design:</strong> Deep understanding of signal integrity, power integrity, and EMI/EMC mitigation for high-speed digital and RF circuits.</p><p style=\"min-height:1.5em\"><strong>- Bring-up &amp; Validation:</strong> Experience with lab equipment (oscilloscopes, spectrum analyzers, logic analyzers) to lead initial board bring-up, debugging, and hardware validation.</p><p style=\"min-height:1.5em\"><strong>- Power Management:</strong> Experience designing efficient power delivery networks (PDN), including DC-DC converters, LDOs, and battery management systems (BMS) for mobile devices.</p><p style=\"min-height:1.5em\"><strong>- Communication Protocols:</strong> Familiarity with CAN, Ethernet, SPI, I2C, UART, USB (2.0/3.0/Type-C), and PCIe, as well as wireless protocols including BLE and Wi-Fi (2.4GHz/5GHz), and the ability to evaluate and debug these systems.</p><p style=\"min-height:1.5em\"><strong>- Cross-functional Collaboration:</strong> Ability to translate ambiguous product goals into hard functional requirements for firmware, mechanical, and research teams.</p><p style=\"min-height:1.5em\"><strong>Bonus Points:</strong></p><p style=\"min-height:1.5em\">- Experience with RF/Antenna integration and FCC/CE certification processes</p><p style=\"min-height:1.5em\">- History of working with JDMs and ODMs</p><p style=\"min-height:1.5em\">- Knowledge of flex-circuit (FPC) design and rigid-flex integration</p><p style=\"min-height:1.5em\">- Experience with robotic actuators or motor control circuitry</p><p style=\"min-height:1.5em\">- Understanding of thermal design optimization and testing<br /></p><p style=\"min-height:1.5em\"><em>Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</em></p>","descriptionPlain":"Who we are\n\nPhysical Intelligence is bringing general-purpose AI into the physical world. We are a team of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.\n\nThe team\n\nThis role is part of the hardware team, but will involve deep collaboration with the embedded firmware team and the robot software engineering (runtime) team.\n\nIn this role you will:\n\n- Drive Hardware Architecture: Lead the electrical design of devices crucial to PI’s data collection, from component selection (SoCs, Sensors, PMICs) to final PCBA.\n\n- Imaging System Design: Lead the hardware integration of high-resolution image sensors, ensuring clean power rails and high-speed data paths (MIPI) for optimal image quality.\n\n- Wireless Hardware Integration: Design and optimize RF front-ends for wireless modules, focusing on antenna placement, signal range, and power consumption.\n\n- Schematic & Layout: Take full ownership of schematics and supervise/execute PCB layouts for complex, space-constrained enclosures.\n\n- Hardware Validation: Design and execute test plans to identify hardware bugs, signal integrity issues, and thermal bottlenecks.\n\n- DFM/DFT: Work with manufacturing partners to ensure designs are optimized for high-yield assembly (Design for Manufacturing) and comprehensive on-line testing (Design for Test).\n\n- Power Optimization: Analyze and optimize the hardware-level power consumption for battery-operated devices, and assist with thermal testing and validation of the devices.\n\nWhat we hope you'll bring:\n\nCompetencies and Skills\n\nIn addition to 3–7 years of experience in hardware design and board-level development for high-volume products, strong candidates must have:\n\n- BS/MS in Electrical Engineering or a related technical field.\n\n- PCB Design Expertise: Proficiency in EDA tools (e.g., Altium, Allegro) for complex, multi-layer, high-density interconnect designs, and experience with rigid flex circuits\n\n- Camera System Experience: Hands-on experience with CMOS image sensors, MIPI CSI-2/3 interfaces, and the electrical requirements for high-bandwidth imaging data, including bring-up and image tuning\n\n- High-Speed Design: Deep understanding of signal integrity, power integrity, and EMI/EMC mitigation for high-speed digital and RF circuits.\n\n- Bring-up & Validation: Experience with lab equipment (oscilloscopes, spectrum analyzers, logic analyzers) to lead initial board bring-up, debugging, and hardware validation.\n\n- Power Management: Experience designing efficient power delivery networks (PDN), including DC-DC converters, LDOs, and battery management systems (BMS) for mobile devices.\n\n- Communication Protocols: Familiarity with CAN, Ethernet, SPI, I2C, UART, USB (2.0/3.0/Type-C), and PCIe, as well as wireless protocols including BLE and Wi-Fi (2.4GHz/5GHz), and the ability to evaluate and debug these systems.\n\n- Cross-functional Collaboration: Ability to translate ambiguous product goals into hard functional requirements for firmware, mechanical, and research teams.\n\nBonus Points:\n\n- Experience with RF/Antenna integration and FCC/CE certification processes\n\n- History of working with JDMs and ODMs\n\n- Knowledge of flex-circuit (FPC) design and rigid-flex integration\n\n- Experience with robotic actuators or motor control circuitry\n\n- Understanding of thermal design optimization and testing\n\n\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records."}],"apiVersion":"1"}