At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
You will build the base intelligence layer for robotics. We train large-scale robot foundation models from massive multimodal datasets spanning video, proprioception, action traces, language, and more. You will design and run the core large-scale training efforts that give our models fundamentally new general capabilities across embodiments, tasks, and environments. You will “live and breathe” all forms of robot data.
If you have worked on pretraining large-scale ML systems or generative foundation models e.g. multimodal, language, audio, etc. (not only robotics), then this may be the role for you.
You’ll be responsible for:
Designing and executing large-scale pretraining runs for robot foundation models (transformer- and diffusion-based architectures)
Defining model architectures, objectives, and training curricula across multimodal robotic data (vision, action, state, language)
Developing scalable data mixtures and sampling strategies across petabyte-scale datasets
Guiding data collection operations towards new directions, as well as sourcing new datasets
Running ablations to understand scaling laws, data quality effects, and architecture tradeoffs
Collaborating closely with ML Infra and Systems to push cluster utilization, throughput, and reliability
Turning raw robotic interaction data into generalizable model capabilities
You might thrive in this role if you:
Have worked on large-scale ML systems with senior/staff (L6+) experience.
Have deep experience training large transformer or diffusion models at scale (for generative models e.g. including language models, audio models, or video models)
Have led or significantly contributed to multi-node, multi-GPU distributed training efforts
Have worked on scaling laws, optimization dynamics, and large-model failure modes
Have strong PyTorch fundamentals and comfort debugging at every layer of the stack
Care about both empirical rigor and raw iteration speed
Are excited about building general-purpose robot intelligence from first principles
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
This is a customer-facing product engineering role with many PM-like responsibilities.
You will build the applications that customers, deployment partners, researchers, and other internal teams will use to diagnose, teach, QA, and run our robots.
You will spend 1/4 of your time with customers learning about their use cases and distilling product requirements. You'll then be one of the key people responsible for implementing those product ideas.
Today, the product surface areas are web UIs, APIs, hardware appliances, robot interfaces, and human processes. You'll be expected to seamlessly work across all parts of the stack.
You’ll be responsible for:
Crafting external and internal API interfaces that customers and partners interface with to access Generalist systems
Building the tools and workflows that enable and accelerate the core missions of researchers, engineers, and operations partners company-wide.
The primary web application researchers, ops, and deployments use to evaluate and train robot models
You might thrive in this role if you:
Have strong intuitions for what makes for great user interfaces, and user experiences
Understand modern web stack technologies: Typescript, React, FastAPI, Postgres, AWS
Understand how to expertly manage and leverage modern AI coding agents to accelerate development while maintaining high quality production standards
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
This role broadly owns infrastructure across the stack. If it’s running in the cloud, you probably care about it. The life blood of robotics is data, and we need high scale infrastructure to manage, store, and process petabytes of this data. Our APIs, services, and monitoring systems depend on the infrastructure you’ll be managing.
You’ll be responsible for:
The compute (both CPU and GPU compute) that’s required to cost effectively process petabytes of data at high throughput
The infrastructure required to process and store petabytes of data
Maintaining the security posture of our infrastructure and data
You might thrive in this role if you:
Have at least 5 years of experience managing high scale cloud infrastructure via tools like Kubernetes, and Terraform. Our services are predominantly in Python
Strong familiarity with AWS services (or their cloud equivalents), and their permission models
Strong opinions on how to properly use coding agents in an infrastructure setting
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
Generalist trains very large robot foundation models. This requires utilizing very large numbers of the latest generation GPU hardware and infrastructure (currently Nvidia) to run distributed training jobs and researcher experiments. We have extreme requirements on storage and data loading infrastructure that requires maximizing cloud infrastructure and custom solutions.
You will also own inference infrastructure. For our robots this is a fleet of on-prem GPUs attached to robots that have extreme real-time and latency budgets in compute constrained environments.
You’ll be responsible for:
Owning our GPU compute fleets
Ensure our GPUs are easy for researchers to use and maximally utilized
Optimizing and improving ML data loading transport and storage in highly distributed fully utilized environments.
Orchestration of robot inference fleets
You might thrive in this role if you:
Have managed large fleets of GPUs doing large-scale, long-term, highly distributed training runs or inference
Deep experience in Slurm or Kubernetes for ML workload orchestration
Have build high-scale ML data loaders and preparation systems
Deeply understand every layer of the ML hardware, storage, and networking stacks
Have experience in the NVidia GPU ecosystem
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
We internally call this team MBMB (More Big More Better). You will own optimizations on both the training and on-robot inference stacks. We are still in a regime of step-function, not incremental, gains.
You’ll be responsible for:
Making GPUs go brrrrr
Implementing ML, hardware, and software changes that lead to step-function gains
Optimizing both the inference and training stacks
You might thrive in this role if you:
Are proficient and stay current with the latest ML techniques for training and inference optimizations in transformer and diffusion based architectures
Will chase ML optimizations anywhere: From the CUDA kernels, to ML architecture, to frontend or backend network bottlenecks, CPU bottlenecks, NVLink and comms, to torch, numpy, and Python inefficiencies.
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
You will own the software that controls our robots. You will collaborate with ML to turn output intentions into smooth, efficient, safe, and responsive actions on a variety of robot embodiments. You will collaborate with hardware and partners to ensure the system, dynamics, and components are behaving optimally.
You’ll be responsible for:
Designing, implementing, and testing the entire real-time control system from the low-level firmware to the input spec for each embodiment we have
Ownership over a wide variety of robot embodiments from stock industrial co-bot arms to custom hardware
You might thrive in this role if you:
Have extensive experience in rigid body kinematics, and robotic controls
Have experience bringing robots into production environments with stringent reliability requirements
Are experienced in high performance, production-ready Python and C++
Experience with kinematics/simulation libraries
Have experience in robotic middleware platforms such as ROS/ROS2/ZCM
Successful candidates have extensive experience (5+ years), often including a PhD
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
This is a deeply cross-functional, execution-oriented ops role at the center of our model research and robotics stack.
As a member of the Robot Science Operations staff, you will help turn robots, data, models, and evaluations into a tight, high-velocity feedback loop for model science. Foundation model intelligence is only as good as the evaluations we can hill climb on, and this role is responsible for making those evaluations real, reliable, and repeatable.
You will execute experiments directed by our research teams on a variety of robot platforms. You will help design tasks, coordinate robot data collection, kick off training jobs, run evaluations, analyze results, and ensure robots are physically ready for rollouts. You may build physical benchmarks, lightly modify hardware setups, test third-party tooling, and write documentation that enables others to replicate and scale your work.
Executing a range of experiments on our robot platforms
Collaborate closely with the research teams on results and be required to synthesize and interpret your findings
Designing new robotic tasks and benchmarks to evaluate model capabilities
Procuring materials and building lightweight physical benchmarks
Ensuring robots are properly configured, calibrated, and ready for rollouts and evaluations
Running structured evaluations and measuring real-world success rates
Analyzing results and closing feedback loops with ML researchers
Beta testing internal and third-party tools for teaching robots new skills
Writing clear documentation and playbooks so others can reproduce workflows
Identifying operational bottlenecks and improving system throughput end-to-end
Be continuously diligent in the face of seemingly repetitive, but subtly changing task evaluations.
Have hands-on experience with robot data collection, evaluation, or deployment
Have conceptual understanding of the full modern ML training, fine-tuning, and inference life cycles
Are comfortable running experiments and tracking real-world metrics across multiple model variants
Enjoy operating across software, hardware, and physical systems
Have some exposure to basic EE/ME tasks (wiring, mounting sensors, assembling fixtures, debugging hardware)
Are highly organized and can coordinate multiple moving parts simultaneously
Write clear, structured documentation
Prefer execution and iteration speed over theoretical purity
Like being the person who “just makes it work”
You will be a part of the ML team, and working very closely with ML, brainstorming ideas, and may prototype as well. However:
This is not a pure ML research role focused on designing new model architectures or advancing core learning algorithms.
This is not a large-scale infrastructure engineering role building distributed systems, databases, or UI platforms.
This is not a deep robotics controls or firmware engineering role.
Instead, this role sits at the intersection of ML, robotics, and operations. You are ensuring our systems run end-to-end in the real world, and improving them through tight execution loops.
If you are most excited by hands-on iteration, cross-functional execution, and accelerating the entire system this role may be a strong fit.
","descriptionPlain":"\nABOUT GENERALIST\n\nAt Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.\n\nWe build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.\n\nThe company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, https://research.google/blog/palm-e-an-embodied-multimodal-language-model/ RT-2 https://deepmind.google/blog/rt-2-new-model-translates-vision-and-language-into-action/, Gemini Robotics https://deepmind.google/models/gemini-robotics/), launched and scaled ChatGPT https://chatgpt.com/ and GPT-4 https://openai.com/index/gpt-4-research/ to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas https://bostondynamics.com/atlas/, Spot https://bostondynamics.com/products/spot/, Stretch https://bostondynamics.com/products/stretch/) and pushed the limits of what they can do (from parkour https://www.youtube.com/watch?v=tF4DML7FIWk to manipulation https://bostondynamics.com/blog/large-behavior-models-atlas-find-new-footing/, and testing robustness https://www.youtube.com/watch?v=aFuA50H9uek).\n\nWe are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.\n\n\nABOUT THE ROLE:\n\nThis is a deeply cross-functional, execution-oriented ops role at the center of our model research and robotics stack.\n\nAs a member of the Robot Science Operations staff, you will help turn robots, data, models, and evaluations into a tight, high-velocity feedback loop for model science. Foundation model intelligence is only as good as the evaluations we can hill climb on, and this role is responsible for making those evaluations real, reliable, and repeatable.\n\nYou will execute experiments directed by our research teams on a variety of robot platforms. You will help design tasks, coordinate robot data collection, kick off training jobs, run evaluations, analyze results, and ensure robots are physically ready for rollouts. You may build physical benchmarks, lightly modify hardware setups, test third-party tooling, and write documentation that enables others to replicate and scale your work.\n\n\n\n\nYOU’LL BE RESPONSIBLE FOR:\n\n - Executing a range of experiments on our robot platforms\n\n - Collaborate closely with the research teams on results and be required to synthesize and interpret your findings\n\n - Designing new robotic tasks and benchmarks to evaluate model capabilities\n\n - Procuring materials and building lightweight physical benchmarks\n\n - Ensuring robots are properly configured, calibrated, and ready for rollouts and evaluations\n\n - Running structured evaluations and measuring real-world success rates\n\n - Analyzing results and closing feedback loops with ML researchers\n\n - Beta testing internal and third-party tools for teaching robots new skills\n\n - Writing clear documentation and playbooks so others can reproduce workflows\n\n - Identifying operational bottlenecks and improving system throughput end-to-end\n\n\nYOU MIGHT THRIVE IN THIS ROLE IF YOU:\n\n - Be continuously diligent in the face of seemingly repetitive, but subtly changing task evaluations.\n\n - Have hands-on experience with robot data collection, evaluation, or deployment\n\n - Have conceptual understanding of the full modern ML training, fine-tuning, and inference life cycles\n\n - Are comfortable running experiments and tracking real-world metrics across multiple model variants\n\n - Enjoy operating across software, hardware, and physical systems\n\n - Have some exposure to basic EE/ME tasks (wiring, mounting sensors, assembling fixtures, debugging hardware)\n\n - Are highly organized and can coordinate multiple moving parts simultaneously\n\n - Write clear, structured documentation\n\n - Prefer execution and iteration speed over theoretical purity\n\n - Like being the person who “just makes it work”\n\n\nWHAT THIS ROLE IS NOT\n\nYou will be a part of the ML team, and working very closely with ML, brainstorming ideas, and may prototype as well. However:\n\n - This is not a pure ML research role focused on designing new model architectures or advancing core learning algorithms.\n\n - This is not a large-scale infrastructure engineering role building distributed systems, databases, or UI platforms.\n\n - This is not a deep robotics controls or firmware engineering role.\n\nInstead, this role sits at the intersection of ML, robotics, and operations. You are ensuring our systems run end-to-end in the real world, and improving them through tight execution loops.\n\nIf you are most excited by hands-on iteration, cross-functional execution, and accelerating the entire system this role may be a strong fit.","compensation":{"compensationTierSummary":"$150K – $200K • Offers Equity","scrapeableCompensationSalarySummary":"$150K - $200K","compensationTiers":[{"id":"9c6b173e-8035-49a8-ad98-5f358129e08d","tierSummary":"$150K – $200K • Offers Equity","title":null,"additionalInformation":null,"components":[{"id":"de78a864-7200-4e90-a09a-ddacb2dec380","summary":"Offers Equity","compensationType":"EquityPercentage","interval":"NONE","currencyCode":null,"minValue":null,"maxValue":null},{"id":"9651b5ca-836b-4452-904f-9ccd962e0554","summary":"$150K – $200K","compensationType":"Salary","interval":"1 YEAR","currencyCode":"USD","minValue":150000,"maxValue":200000}]}],"summaryComponents":[{"compensationType":"EquityPercentage","interval":"NONE","currencyCode":null,"minValue":null,"maxValue":null},{"compensationType":"Salary","interval":"1 YEAR","currencyCode":"USD","minValue":150000,"maxValue":200000}]}},{"id":"fc7c7b49-248a-4849-a473-a0bd246e5486","title":"Research Assistant","department":"Technical Staff","team":"Technical Staff","employmentType":"FullTime","location":"San Francisco Bay Area (San Mateo) or Boston (Somerville)","shouldDisplayCompensationOnJobPostings":true,"secondaryLocations":[],"publishedAt":"2026-06-25T22:53:50.096+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressCountry":"United States"}},"jobUrl":"https://jobs.ashbyhq.com/generalist/fc7c7b49-248a-4849-a473-a0bd246e5486","applyUrl":"https://jobs.ashbyhq.com/generalist/fc7c7b49-248a-4849-a473-a0bd246e5486/application","descriptionHtml":"At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
We are looking for a Research Assistant to help design, run, and analyze experiments at the intersection of machine learning and robotics. This is an entry-level research role for individuals with less than 3 years of machine learning research experience, and is designed to be a potential career path towards eventually contributing as a Research Scientist.
At Generalist, we are building foundation models for robots. These models improve through a tight feedback loop: design experiments, collect data, train or fine-tune models, evaluate them in the real world, analyze results, and repeat. This role helps make that loop faster, more rigorous, and more reliable.
You will work closely with ML researchers and robotics engineers to run robot experiments, design evaluation tasks, brainstorm ideas, collect data, interpret results, and document repeatable workflows.
A major part of this role is helping ensure our evaluations are trustworthy. We care deeply about experimental design, controls, hands-on iteration, sample sizes, variance, repeatability, and statistical rigor.
Running structured experiments on robot platforms
Setting up physical tasks, materials, fixtures, and benchmarks for robot evaluations
Collecting high-quality robot data and tracking experimental conditions
Measuring real-world success rates across tasks, robots, and model variants
Designing evaluations with attention to controls, repeatability, statistical rigor, and sources of bias
Analyzing results to help distinguish real model improvements from noise
Synthesizing findings and communicating them clearly to ML researchers and engineers
Preparing robots, sensors, workspaces, and materials for rollouts and evaluations
Helping kick off training jobs, run evaluations, and organize results
Beta testing internal and third-party tools for teaching robots new skills
Troubleshooting physical setups, hardware issues, and procedural bottlenecks
Writing clear documentation and playbooks so others can reproduce workflows
Improving experimental reliability, data quality, and operational throughput over time
Have experience running experiments, lab studies, field studies, data collection workflows, or structured evaluations
Think carefully about experimental design, confounding factors, controls, sample sizes, variance, and what conclusions the data can actually support
Are diligent and detail-oriented, especially when tasks are repetitive but subtle differences matter
Enjoy hands-on work with physical systems, equipment, materials, or instruments
Are comfortable following protocols while also noticing when something is wrong or could be improved
Can coordinate many moving parts: robots, materials, tasks, data, model versions, metrics, and documentation
Communicate clearly and can summarize what happened, what changed, and what the evidence suggests
Are curious about machine learning and robotics, even if you are not yet an expert in either
Have some exposure to programming, data analysis, robotics, hardware, electronics, mechanical assembly, or experimental tooling
Prefer fast iteration, careful measurement, and empirical progress over abstract theory alone
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
About the role
Generalist is hiring a Robotics Operations Manager to lead and scale the on-site operations that produce high-quality data for our robotic foundation models. You’ll lead robot operators and shift leads, owning daily execution across staffing, robot readiness, and data collection. Working closely with research and engineering, you’ll turn evolving technical priorities into reliable workflows and build the processes and team capabilities needed to scale.
What you’ll do
Own daily robotics operations. Coordinate staffing, task scheduling, robot availability, and equipment readiness to deliver consistent data collection throughput and quality.
Lead and develop the team. Coach operators and shift leads, set clear expectations, and support hiring, onboarding, training, scheduling, and performance management.
Keep the lab ready and safe. Oversee robot setup, readiness checks, equipment tracking, and safe operating procedures. Stay close to the work on the lab floor, support basic troubleshooting, and coordinate repairs and technical escalations.
Translate research priorities into execution. Partner with research and engineering to launch, refine, and retire data collection tasks, with clear instructions, quality checks, and issue tracking.
Use operational data to improve performance. Establish metrics and reporting across robot utilization, throughput, data quality, operator productivity, and equipment reliability. Identify bottlenecks and recurring failures, then drive improvements with the relevant teams.
Build processes that scale. Develop practical operating procedures, training materials, and handoff routines that help the team execute consistently as the fleet and operation grow.
You might thrive here if you…
Have owned day-to-day execution in robotics, manufacturing, logistics, technical operations, or another hands-on environment where people and equipment must work together reliably.
Have led and developed frontline teams, including coaching people, setting performance expectations, and maintaining standards for quality and safety.
Are comfortable working around complex hardware and can assess an operational problem, guide initial troubleshooting, and recognize when engineering support is needed.
Have used metrics to identify a bottleneck or recurring issue and made changes that improved throughput, quality, or reliability.
Can turn changing technical requirements into clear instructions and daily priorities, making sound decisions and communicating tradeoffs when the process is still taking shape.
Helpful additional experience
Robotics, industrial automation, or managing and maintaining fleets of complex hardware.
AI/ML data collection, human-in-the-loop workflows, or quality assurance in a technical environment.
Building operational dashboards or using automation, scripting, or AI tools to improve workflows.
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
About the Role
Robots that learn from the world need hardware that can see, sense, and act within it. As a Hardware Engineer at Generalist, you will own electrical systems from end-to-end: from napkin sketch of concepts to schematic, layout, bring-up, and production. You’ll be responsible for custom hardware behind the cameras, sensors, and motor control that power our robots and the foundation models behind them.
This is a full stack EE role. In a typical week, you may be prototyping new sensor modules and motor controls, debugging MIPI signal integrity on the bench, writing firmware for a microcontroller, working with a contract manufacturer to push a design through DFM and certification, and managing rollout of new hardware designs to the robot fleet. You will collaborate daily with mechanical engineers on packaging, thermals, and integration; and with software engineers on drivers, interfaces, and system performance.
You’ll be responsible for:
Owning electrical designs through the full lifecycle: concept, architecture, schematic capture, PCB layout, fabrication, bring-up, validation, and scaled production
Designing sensing and motor control electronics for robot systems that are low latency, high fidelity, and robust in challenging environments with industrial interfaces (e.g. RS-485, CAN)
Designing multi-sensor architectures interfacing with highly integrated latest generation SoCs
Architecting power delivery systems with complex power trees and different sources (802.3bt, USB-C PD, LiPo)
Battery charging and power path management within tight power and thermal budgets in compact enclosures
Writing and debugging embedded firmware (C, C++, Rust) on microcontrollers or low level Linux device drivers for bring up, test, and production
Partnering closely with mechanical engineers on enclosure integration, thermal design, connector selection and placement, cabling
Driving designs to production: DFM and DFT, EMC and regulatory certification (FCC, CE), test fixture development, and manufacturing ramp with in-house resources, external design partners, or contract manufacturers
You might thrive in this role if you:
Have 5+ years shipping complex electronics products
Have demonstrated full stack EE ownership: taking ideas from concept to production
Have experience with highly integrated SoC based designs (e.g. Qualcomm, NXP i.MX, Ambarella, etc) including high speed interfaces (e.g. MIPI CSI/DSI, USB 3.x, PCIe)
Have deep experience in one or more of the following: imaging systems (image sensor selection, ISP tuning, frame synchronization), motor control (BLDC drivers, current sensing, encoders)
Have high dynamic range in your work: from thinking deeply about high level system architecture choices and discussing their impact on model performance with our ML engineers, to getting your hands dirty with bench level soldering and rework, measuring timing delays on the oscilloscope, and swapping in new hardware for a live system test
Have experience managing external suppliers, design partners, CM / JDMs, including schedule planning, materials sourcing, and production ramp
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
Embodied foundation models and their capabilities are driven by data — and robotics data does not exist on the internet waiting to be scraped. It has to be manufactured by people doing real work in real environments, to a spec guided by our model science and scaling laws.
You will own the data engine that feeds our models: finding the right partners who can collect at quality and volume, standing them up, supplying them with necessary hardware, and holding them to a bar. Our data partnerships and operations extend globally, and expanding the ecosystem involves building the underlying network infrastructure for data ingestion and distribution that will feed in to support future commercial partnerships as well. Expect to extend the data engine into new geographies and new data modalities on tight timelines.
The hardest part of the job is translating model needs and data requirements into something a data partner can execute without you in the room (and you are the first to catch the drift when what comes back is technically compliant but practically useless).
Data supply strategy. Identify what we need to buy versus build. Map the vendor landscape across data types and quality. Bring recommendations, not options.
Vendor sourcing and diligence. Find, evaluate, and pilot new data partners. Run structured trials before committing volume. Know how to tell a real capability from a good deck.
Requirements elicitation. Sit with ML and engineering leads and extract the actual requirement — volume, environments, embodiments, task diversity, annotation schema, acceptance criteria, what happens downstream. Most of the time the requirement does not exist in writing until you write it.
Translation and specification. Author partner-facing specs that a non-ML operator can execute against with no follow-up call. Define the unit of delivery, what passes, what fails, and what to do when it is ambiguous.
Commercial terms. Structure pricing, rate cards, minimums, milestones, and acceptance language. Work with legal on MSAs and SOWs. Own the unit economics and know what we are paying per unit of usable data, not per unit delivered.
Scaling a partnership into a network. When one partner hits capacity, stand up the next without dropping quality or blowing up cost.
Operating cadence. Trackers, weekly partner reviews, forecasts against the research roadmap, and a clear picture of cost, volume, and quality that anyone at the company can read.
Closing the loop. Report back to research on what the data actually produced and use it to change the next cycle's spec.
Travel. Periodic domestic and international travel to partner sites and collection operations.
6+ years owning external partners or vendors who delivered a product or service to you — supply chain, vendor management, outsourcing/BPO management, data operations, or partnerships with a delivery obligation.
Demonstrated experience standing up a new vendor from zero: selection, diligence, contracting, ramp, and ongoing management.
A track record of translating technical or specialist requirements into unambiguous instructions that a non-technical execution partner delivered against successfully.
Fluency with commercial mechanics — pricing structures, SOWs, acceptance criteria, unit economics — and the judgment to know which terms actually protect quality.
Exceptional written communication. You will write documents that people you have never met execute without you present.
Comfort operating with incomplete requirements and re-scoping mid-flight without losing the relationship.
Even-keeled under pressure and relentlessly consistent on follow-through.
Experience buying or managing data collection, annotation, or labeling at scale — managed workforce, crowd, or BPO.
Experience close to an ML or research organization, and enough working understanding of training data to push back on a request rather than just relay it.
Background in autonomous vehicles, robotics, hardware, or another domain where physical-world data acquisition is a first-class problem.
Experience at a company that grew quickly enough that the process you inherited stopped working and you had to rebuild it.
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
We’re hiring hardware engineers that can advance our goals of developing grippers, sensors, and robotic systems capable of dexterous manipulation that is robust, capable, and precise.
Responsibilities
Develop wearable data collection devices capable of dexterous manipulation, from concept design through mass-production.
Design and manufacture robot hands that include custom structures, actuators, as well as integration of cameras, IMUs, encoders, and additional sensors.
Perform trade studies to evaluate various actuator, robot, and sensor implementations.
Lead engagements with external vendors to manufacture components, assemblies, or to multiply IC efforts.
Integrate COTS and custom robotic arms, robot stands, mobile bases, robotic hands, sensors, and end effectors.
Test designs for functionality, robustness, and compliance with key standards
Collaborate with a multi-disciplinary team that includes ML, controls, perception, operations, mechanical, electrical and hardware engineers; as well as a business development team to define product requirements, timelines, and dynamically set priorities.
Desired Qualifications
Strong experience in design of tightly integrated electro-mechanical systems
Fluency in CAD modeling (Solidworks), PDM, FEA, and physics-driven analysis
Leadership in driving a project from conceptual design through mass production
Injection molding, overmolding, machining, additive manufacturing, actuator assembly, and/or electronics manufacturing experience is beneficial.
10+ years of education/experience in relevant mechanical / electro-mechanical design
Strong communication skills, and a commitment to building a respectful and collaborative environment
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
Pretraining gives us a general model. Post-training makes it useful, controllable, safe, and performant in the real world. You will train large pretrained robot models into production-ready systems via fine-tuning, reinforcement learning, steering, human feedback, task specialization, evaluation, and on-robot validation—at scale. Regardless of your initial background, you will grow into becoming a full-stack ML roboticist capable of quickly pinpoint issues on either side of ML or controls, and all the places in between. This is where research meets reality.
You’ll be responsible for:
Designing fine-tuning and adaptation strategies for downstream robotic tasks and embodiments
Developing methods for improving reliability, robustness, and controllability
Building evaluation frameworks that measure real-world robot performance, not just offline metrics
Improving inference-time performance (latency, stability, memory footprint) in collaboration with ML infrastructure
Leveraging techniques such as imitation learning, RL, distillation, synthetic data, and curriculum learning
Closing the loop between model outputs and physical-world outcomes
You might thrive in this role if you:
Have experience with fine-tuning large models for downstream tasks (RLHF, IL, RL, distillation, domain adaptation, etc.)
Have worked on embodied AI, robotics, or real-world ML systems
Care deeply about evaluation, benchmarking, and failure analysis
Are comfortable debugging across the ML stack — from loss curves to robot behavior
Enjoy rapid iteration with real-world feedback loops
Want to bridge the gap between foundation models and physical deployment
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
We are actively building our teams across research science, ML infrastructure, robotics controls, hardware, data operations, and go-to-market. Most of these roles are senior, and we focus heavily on reaching talented professionals who may not be actively job-seeking.
This role is about creating thoughtful talent strategies and intentionally mapping candidate ecosystems rather than simply focusing on volume.
Partnering closely with our Head of Talent Acquisition, you will help design and scale our hiring engine. For any given domain, you will develop a deep understanding of key contributors, influential research, impactful engineering work, and upcoming career milestones. You will bring these insights to hiring managers with a clear perspective to help attract and engage top talent.
Equally important is your internal partnership. Our hiring managers are primary researchers and engineers who value efficient, data-informed guidance. By sharing clear pipeline metrics, channel insights, and candidate feedback, you will build strong trust with technical leaders and continuously refine our hiring practices.
As one of the initial members of our talent team, you will have a unique opportunity to lay the groundwork, lead priority searches, and shape our overall recruiting methodology from the ground up.
End-to-end search ownership. Manage intake, strategy, sourcing, screening, loop design, closing, and seamless handoffs to onboarding across key critical searches.
Proactive talent mapping. Map target domains early to identify prospective candidates thoughtfully, especially in areas where our network is still expanding.
Targeted sourcing. Explore publications, conferences, repositories, and referral networks to craft meaningful, highly personalized candidate outreach.
Modern tooling & AI integration. Leverage AI tools for research, enrichment, and workflow enhancement while maintaining high accuracy and sound quality standards.
Data-informed insights. Track pipeline conversion, channel effectiveness, and feedback loops to guide team decisions and optimize our overall strategy.
Hiring manager partnership. Collaborate closely on role scoping, calibration, interview loops, interviewer preparation, and debrief facilitation.
Candidate engagement & closing. Articulate our mission, technical scope, and team density to effectively invite candidates to join our growth journey.
Structured operations. Maintain clean data, reliable scheduling, and structured interviewing practices within Ashby to ensure an efficient experience for everyone.
External partnerships. Collaborate with and manage external agencies effectively to supplement internal sourcing capabilities as needed.
Multi-site collaboration. Support in-person hiring efforts across our San Francisco and Boston locations, including occasional site visits and key industry events.
5+ years full-cycle technical recruiting,
A track record of closing senior technical hires who had competing offers — with specifics you can walk us through.
Real passive-sourcing depth. You have built named-target searches from a blank page in a domain you did not previously know, and hired from them.
Data fluency. You can build a funnel, find the leak, and use the result to change a hiring manager's mind. Comfort with ATS reporting and with a spreadsheet you built yourself.
Working, current use of AI tooling in your own workflow, with judgment about where it helps and where it fabricates.
Exceptional written communication. Outreach, briefs, and internal recommendations that get read and acted on.
Genuine technical curiosity. You do not need to have trained a model, but you should want to know why one architecture beat another, and you should be able to read an abstract and work out whether the author is relevant to us.
Strong relationship management under pressure — candidates, hiring managers, and agencies — while holding a bar.
Based in San Francisco or Boston, in person.
Hiring for a frontier research organization or AI lab: research scientists, pre-training and post-training, RL, ML infrastructure.
Robotics, autonomous vehicles, or hardware — anywhere the physical world constrains what the software can do.
Experience as an early or founding recruiter, where you built the function and not just the pipeline.
Ashby, or fluency in a comparable structured-interview ATS and a view on what makes one good.
Agency or search-firm training early in your career, combined with in-house judgment later.
Familiarity with both the Bay Area and Boston markets, which behave differently and are not staffed the same way.
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
At Generalist, we build foundation models for the physical world. Across our team in San Mateo and Boston, we know that our company’s future is shaped entirely by the people who join us. That’s why we care deeply about making every candidate feel welcomed, valued, and respected from their very first conversation to their very first day on the job.
As our Recruiting Coordinator, you’ll be the heart of that candidate experience!
You will serve as our operational anchor, bringing warmth, organization, and clarity to interview scheduling, candidate communication, and overall hiring logistics. Sitting at the intersection of every team at Generalist, you'll play a vital role in building our culture and company.
You will be in the San Mateo office five days a week.
Here’s what you’ll be doing:
Lead the scheduling of all interview stages — from initial chats and screens to full on-sites — across San Mateo, Boston, and candidate time zones using Ashby.
Be the main guide and friendly contact for candidates throughout their journey, ensuring every touchpoint feels thoughtful, well-organized, and seamless.
Coordinate travel and expenses for visiting candidates, ensuring flights, hotel stays, ground transit, and reimbursements are effortless for them.
Keep Ashby running smoothly and reliably — maintaining stage accuracy, interview plans, email templates, direct-booking links, and interviewer training records.
Support interviewer balance across our team by distributing schedules fairly and flagging early when we need to expand our interviewer pool.
Keep pipelines flowing effortlessly by spotting potential bottlenecks, resolving delays, and troubleshooting scheduling conflicts proactively.
Partner on offer logistics — from background checks and Ashby offer packets to sending personalized welcome notes and swag — ensuring a delightful handoff to HR and IT for day one.
Treat candidate privacy with utmost care and discretion at every step of the process.
Continuously refine our recruiting tools, templates, and workflows to make our interview operations increasingly efficient and candidate-friendly.
You might thrive in this role if you:
Have 1+ year(s) coordinating interviews at volume, or comparable experience — an EA supporting several executives, or an operations role where you owned complex multi-party scheduling and the consequences of getting it wrong.
Have worked in Ashby and know its scheduling, interview plans, templates, and interviewer pools well enough to have opinions about how they should be set up.
Write unusually well in short forms. A reschedule email from you makes a candidate feel taken care of rather than processed, and a note to a hiring manager tells them exactly what you need in three lines.
Are precise by disposition. Names spelled correctly, links tested before they are sent, time zones right the first time, and no interview that starts with five minutes of confusion.
Demonstrated ability to manage competing priorities and adjust quickly when schedules shift, candidates re-route, or hiring needs change.
Genuine customer service orientation – you treat every candidate, hiring manager, and interviewer like the most important person in your inbox.
Interest in a long-term career in People, Talent, or HR – with curiosity about how recruiting operations scale as a company grows.
Are energized by being in the office five days a week and want to be in the room on the days that matter.
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
Generalist is looking for a Strategic Deals Lead to own the structuring, negotiation, and expansion of our most important commercial and strategic relationships.
As we bring frontier robotics technology into the real world, many of our partnerships do not fit neatly into standard software or commercial agreements. They involve new technologies, evolving business models, complex technical and legal considerations, and counterparties ranging from large global enterprises to robotics and technology partners.
You will be part of our Applied AI & Partnerships team, working closely with technical and executive leadership to turn strategic relationships into durable, scalable commercial agreements. You should be equally comfortable designing a creative deal structure, negotiating with a senior business executive, working through a difficult contractual issue, and getting deep enough into our technology to understand what the agreement needs to protect and enable.
Responsibilities
Strategic deal ownership: Own the structuring, negotiation, and closing of Generalist’s most complex and strategically important commercial transactions and partnerships, from initial terms through definitive agreements, renewals, and expansions.
Commercial structuring: Develop creative deal structures for emerging technologies and business models, balancing strategic value, economics, technical feasibility, customer needs, and long-term company interests.
Negotiation & legal terms: Lead commercial negotiations and partner closely with legal counsel on complex contractual issues, including training data and data-use rights, model and fine-tune rights, intellectual property, exclusivity, deployment, and other emerging AI and robotics concepts.
Technical & cross-functional partnership: Work closely with Applied AI & Partnerships, company leadership, and technical teams to understand the technology and translate product, model, data, and deployment requirements into appropriate deal structures and commitments.
Renewals & expansion: Drive the commercial strategy for major partnership renewals and expansions, identifying opportunities to deepen relationships and increase their long-term value.
Deal strategy & playbooks: Synthesize learnings from transactions into clear recommendations for leadership, including reusable negotiation positions, deal frameworks, market intelligence, and implications for future commercial strategy.
Minimum Qualifications
Demonstrated track record of independently structuring, negotiating, and closing complex, high-value technology transactions or strategic partnerships.
Significant experience negotiating agreements involving novel technologies, non-standard commercial structures, or complex intellectual property and data considerations.
Strong commercial judgment and the ability to distinguish between issues that are strategically critical and those where creative compromise is possible.
Ability to understand sophisticated legal concepts, work closely with technical teams and translate complex engineering and product concepts into commercial structures, contractual requirements, and strategic recommendations.
Excellent written and verbal communication skills, including the ability to distill complex negotiations into clear decisions and recommendations for senior leadership.
Ability to operate effectively under pressure, build alignment among stakeholders with competing objectives, and know when to challenge, escalate, develop alternatives, or close.
Comfort operating in a fast-changing environment where priorities, processes, and responsibilities may sometimes be ambiguous and evolve quickly.
8–10+ years of experience in strategic deals, corporate development, strategic partnerships, business development, technology transactions, or a related field, with meaningful direct transactional ownership.
Experience negotiating transactions involving AI, machine learning, robotics, enterprise software, data licensing, intellectual property, or other technically complex products.
Experience owning renewals and expansions of large strategic or enterprise. relationships.
Experience working in an environment where the product, business model, and market structure are still evolving.
JD preferred.
Experience managing multiple high-value transactions simultaneously at different stages of maturity and commercial development.
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
Partner relationships: Serve as a high-energy point of contact for prospective partners, communicating Generalist’s technology and vision clearly, building strong relationships, and identifying opportunities for meaningful partnerships.
Technical fluency: Become a super user of Generalist’s models and technology, developing the technical fluency to explain complex concepts clearly, demonstrate capabilities, identify compelling use cases, and help partners understand what is possible.
Partnership qualification & development: Evaluate partnership opportunities, quickly understand partner needs and potential value, prioritize the strongest opportunities, and move promising relationships toward concrete next steps.
Project management: Own partner initiatives end-to-end, translating conversations into clear workplans, owners, milestones, and timelines and keeping internal and external stakeholders moving toward outcomes.
Communication & organization: Bring exceptional organization and written and verbal communication to a high volume of parallel partner workstreams; synthesize complex technical and business topics into clear partner-facing communication, internal updates, decisions, and next steps.
Cross-functional coordination: Work closely with ML/engineering, product, GTM, and leadership to coordinate partner needs, surface decisions, minimize internal overhead, and ensure strong follow-through.
Travel & ecosystem engagement: Represent Generalist with partners and at relevant industry events and conferences as needed.
Minimum Qualifications
2–5 years of professional experience in a highly demanding, high-ownership environment, such as a technology company, startup, management consulting, or similar, with a track record of delivering high-quality work on tight timelines.
Proven ability to own and drive multiple cross-functional initiatives simultaneously, create clarity from ambiguity, and execute end-to-end with minimal oversight.
Exceptional organizational and project management skills; able to manage a high volume of parallel conversations and workstreams without losing track of details, owners, timelines, or follow-up.
Exceptional written and verbal communication skills, including the ability to understand complex technical concepts and explain them clearly and compellingly to different audiences.
Strong technical curiosity and demonstrated ability to quickly develop fluency in complex products or technologies.
High energy, responsiveness, and strong interpersonal skills; genuinely enjoys meeting new people, building relationships, and representing technology enthusiastically with external partners.
Strong judgment and ability to quickly assess opportunities, prioritize where to invest time, and drive conversations toward clear next steps.
High integrity, reliability, and consistent follow-through.
Comfort operating in a fast-changing environment where priorities, processes, and responsibilities may sometimes be ambiguous and evolve quickly.
Experience working in AI/ML, robotics, developer platforms, or another complex technical environment.
Experience owning partner or customer engagements from initial conversation through execution and ongoing success.
Experience in partnerships, business development, product/program management, strategy & operations, or another role combining external relationships with operational execution.
Demonstrated ability to craft clear external narratives and crisp internal decision memos for high-visibility workstreams.
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
Partner ownership: Own and deepen relationships with a small number of Generalist’s most important partners, building trusted relationships across technical, operational, and executive stakeholders.
Partnership development: Evaluate partnership opportunities for both new and current partners, including understanding priorities, identifying opportunities for collaboration, and translating into concrete next steps.
Technical fluency: Become a super user of Generalist’s models and technology, developing the technical depth to explain complex concepts clearly, engage credibly with partner teams, identify compelling applications, and help partners get the most out of our technology.
Program leadership: Drive complex partner initiatives end-to-end, aligning stakeholders across organizations, defining workplans and milestones, resolving blockers, and maintaining momentum across multiple workstreams.
Executive communication: Communicate clearly and credibly with senior internal and external stakeholders, synthesizing technical and business topics into crisp updates, recommendations, decisions, and next steps.
Cross-functional coordination: Work closely with ML/engineering, product, Partnerships, and leadership to represent partner needs internally, coordinate decisions, and translate external learnings into product, model, and company action.
Travel: Represent Generalist with partners and at relevant industry events and conferences as needed.
Minimum Qualifications
5–7 years of professional experience in partnerships, business development, product/program leadership, strategy & operations, technology, or another high-ownership environment.
Demonstrated ability to independently own important external relationships and complex cross-functional initiatives with minimal oversight.
Exceptional organizational and project management skills; able to manage multiple high-stakes workstreams, stakeholders, decisions, and timelines simultaneously.
Exceptional written and verbal communication skills, including the ability to understand complex technical concepts and explain them clearly and compellingly to different audiences.
Strong technical curiosity and demonstrated ability to quickly develop fluency in complex products or technologies.
Strong judgment and ability to understand partner needs, identify the highest-value opportunities, navigate ambiguity, and make thoughtful recommendations.
Strong interpersonal skills and executive presence; able to build trust with stakeholders across different levels and functions within large organizations.
High ownership, integrity, responsiveness, reliability, and consistent follow-through.
Comfort operating in a fast-changing environment where priorities, processes, and responsibilities may sometimes be ambiguous and evolve quickly.
Experience working in AI/ML, robotics, developer platforms, enterprise technology, or another complex technical environment.
Experience owning major customer or partner relationships over multiple years and expanding those relationships over time, including working directly with senior executives and navigating complex enterprise organizations.
Experience leading technical programs or deployments involving multiple internal and external teams.
Experience working in an early- or growth-stage technology company where roles and processes are still evolving.
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
The ideal candidate has strong foundational experience in commercial and corporate law, but is also deeply interested in emerging technology. You should be comfortable working through questions where there may be limited precedent, particularly around AI, machine learning, data, privacy, intellectual property, and new technology business models.
Commercial & strategic transactions: Draft, review, and negotiate commercial agreements, including strategic partnerships, customer and vendor contracts, pilots, SOWs, NDAs, and other technology transactions; support complex negotiations with Partnerships and company leadership.
Corporate & fundraising: Support financings, fundraising, corporate governance, board and stockholder matters, diligence, and other corporate workstreams, coordinating with external counsel as needed.
AI, data & technology: Advise on legal issues related to Generalist’s technology, including training data, data-use rights, models and fine-tunes, intellectual property, confidentiality and privacy, deployment, and other emerging AI and robotics issues.
Legal advice & risk management: Serve as a practical legal advisor across the company, translating legal risk into clear recommendations that help teams move quickly and make sound decisions.
Legal infrastructure & external counsel: Build scalable templates, playbooks, policies, and processes, and manage outside counsel where specialized support is needed.
Emerging legal landscape: Stay current on developments in AI, LLMs, robotics, privacy, intellectual property, regulation, market practices, and contractual precedent, and take on new legal issues as they arise.
Minimum Qualifications
JD and active membership in at least one U.S. state bar.
6–10+ years of relevant legal experience, including meaningful experience at a technology company, technology-focused law firm, or both.
Strong experience drafting and negotiating commercial technology agreements.
Ability to independently identify legal issues, assess risk, develop a recommendation, and drive matters to resolution without requiring significant day-to-day supervision.
Strong grounding in corporate and commercial law, with the ability to work across a broad range of legal issues rather than specializing narrowly in a single area.
Ability to understand complex technical concepts, work effectively with engineering and research teams, and advise on technology, data, intellectual property, privacy, or related legal issues.
Excellent commercial judgment and an ability to give clear, practical advice rather than simply identifying legal risks.
Strong written and verbal communication skills, including the ability to explain complex legal concepts clearly to non-lawyers.
Comfort operating in a fast-moving environment where the applicable law, market norms, and contractual precedent may still be developing.
Experience working in-house at an AI, machine learning, robotics, software, or other frontier technology company, especially growth-stage startups.
Significant experience leading or supporting complex commercial deals, strategic transactions, financings, acquisitions, investments, and other high-value or high-impact legal transactions from structuring through execution.
Experience negotiating agreements involving AI models, training data, data licensing, model outputs, fine-tuning, intellectual property, or other emerging technology issues.
Familiarity with current commercial and legal practices in generative AI and LLM-related transactions.
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
This is a hands-on, execution-driven role at the center of building, operating, and maintaining our robots.
As a Robotics Technician, you'll work across a wide range of hardware activities — from assembling new robotic systems to troubleshooting, repairing, and improving existing ones. You'll help ensure our robots are built correctly, operate reliably, and remain ready for use.
In practice, you'll assemble mechanical systems, perform electrical work, integrate hardware components, test and troubleshoot robots, and help resolve issues as they arise. One day you might be building a new robot, the next diagnosing a hardware failure, replacing components, or supporting an engineering test.
This role is about being adaptable, solving problems, and helping keep our robotic systems moving forward.
Assembling, integrating, and maintaining robotic systems and hardware
Performing mechanical and electrical work, including wiring, connectors, component installation, and hardware replacement
Diagnosing, troubleshooting, and repairing mechanical and electrical issues
Testing, inspecting, and validating robotic systems to ensure proper functionality and reliability
Using hand tools, power tools, diagnostic equipment, and specialized tools to perform precise technical work
Reading and following technical documentation, assembly instructions, and standard operating procedures
Identifying hardware defects, performance issues, and opportunities for improvement
Supporting engineers with hardware modifications, prototype builds, testing, and integration work
Performing routine maintenance, repairs, and upgrades on existing robotic systems
Documenting work performed, tracking issues, and communicating findings to engineers and teammates
Maintaining a safe, clean, and organized workspace
Contributing to improvements in build processes, maintenance procedures, and overall hardware reliability
Have hands-on experience working with mechanical systems, electronics, robotics, or other complex hardware
Are comfortable using tools to assemble, troubleshoot, modify, and repair physical systems
Have experience or familiarity with basic electrical work, including wiring, connectors, and electrical components
Enjoy figuring out why something isn't working and taking the initiative to fix it
Are detail-oriented and take pride in producing clean, reliable work
Can follow structured instructions while also thinking independently when unexpected issues arise
Are comfortable learning new tools, equipment, and technical processes
Can adapt quickly between different projects and priorities
Are reliable, resourceful, and comfortable working in a fast-moving environment
Enjoy working alongside engineers and other technical teams
Like working with your hands and seeing the direct impact of your work
This is not a purely theoretical or design-focused engineering position
This is not a robotics software or controls engineering role
This is not limited to repetitive assembly or production-line work
This is not a position where you'll only follow instructions without opportunities to solve problems
Instead, this role sits at the intersection of robot assembly, hardware integration, testing, and maintenance. You'll be expected to develop a broad understanding of our robotic systems and contribute wherever hands-on technical support is needed.
As we scale our robotic fleet and hardware capabilities, this role will evolve alongside the complexity of our systems and operations.
You'll have opportunities to develop deeper expertise in robotics, take ownership of increasingly complex technical work, and contribute to improvements in how our robots are assembled, tested, maintained, and supported.
Whether your interests lean toward mechanical systems, electrical integration, troubleshooting, or robotics engineering support, this role offers exposure to a broad range of technical challenges.
If you enjoy building things, solving problems, and working directly with advanced robotic systems, this is an opportunity to make a tangible impact on how real-world robotics scales.
","descriptionPlain":"\nABOUT GENERALIST\n\nAt Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.\n\nWe build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.\n\nThe company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, https://research.google/blog/palm-e-an-embodied-multimodal-language-model/ RT-2 https://deepmind.google/blog/rt-2-new-model-translates-vision-and-language-into-action/, Gemini Robotics https://deepmind.google/models/gemini-robotics/), launched and scaled ChatGPT https://chatgpt.com/ and GPT-4 https://openai.com/index/gpt-4-research/ to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas https://bostondynamics.com/atlas/, Spot https://bostondynamics.com/products/spot/, Stretch https://bostondynamics.com/products/stretch/) and pushed the limits of what they can do (from parkour https://www.youtube.com/watch?v=tF4DML7FIWk to manipulation https://bostondynamics.com/blog/large-behavior-models-atlas-find-new-footing/, and testing robustness https://www.youtube.com/watch?v=aFuA50H9uek).\n\nWe are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.\n\n\nROBOTICS TECHNICIAN\n\n\nABOUT THE ROLE\n\nThis is a hands-on, execution-driven role at the center of building, operating, and maintaining our robots.\n\nAs a Robotics Technician, you'll work across a wide range of hardware activities — from assembling new robotic systems to troubleshooting, repairing, and improving existing ones. You'll help ensure our robots are built correctly, operate reliably, and remain ready for use.\n\nIn practice, you'll assemble mechanical systems, perform electrical work, integrate hardware components, test and troubleshoot robots, and help resolve issues as they arise. One day you might be building a new robot, the next diagnosing a hardware failure, replacing components, or supporting an engineering test.\n\nThis role is about being adaptable, solving problems, and helping keep our robotic systems moving forward.\n\n\nYOU'LL BE RESPONSIBLE FOR:\n\n - Assembling, integrating, and maintaining robotic systems and hardware\n\n - Performing mechanical and electrical work, including wiring, connectors, component installation, and hardware replacement\n\n - Diagnosing, troubleshooting, and repairing mechanical and electrical issues\n\n - Testing, inspecting, and validating robotic systems to ensure proper functionality and reliability\n\n - Using hand tools, power tools, diagnostic equipment, and specialized tools to perform precise technical work\n\n - Reading and following technical documentation, assembly instructions, and standard operating procedures\n\n - Identifying hardware defects, performance issues, and opportunities for improvement\n\n - Supporting engineers with hardware modifications, prototype builds, testing, and integration work\n\n - Performing routine maintenance, repairs, and upgrades on existing robotic systems\n\n - Documenting work performed, tracking issues, and communicating findings to engineers and teammates\n\n - Maintaining a safe, clean, and organized workspace\n\n - Contributing to improvements in build processes, maintenance procedures, and overall hardware reliability\n\n\nYOU MIGHT THRIVE IN THIS ROLE IF YOU:\n\n - Have hands-on experience working with mechanical systems, electronics, robotics, or other complex hardware\n\n - Are comfortable using tools to assemble, troubleshoot, modify, and repair physical systems\n\n - Have experience or familiarity with basic electrical work, including wiring, connectors, and electrical components\n\n - Enjoy figuring out why something isn't working and taking the initiative to fix it\n\n - Are detail-oriented and take pride in producing clean, reliable work\n\n - Can follow structured instructions while also thinking independently when unexpected issues arise\n\n - Are comfortable learning new tools, equipment, and technical processes\n\n - Can adapt quickly between different projects and priorities\n\n - Are reliable, resourceful, and comfortable working in a fast-moving environment\n\n - Enjoy working alongside engineers and other technical teams\n\n - Like working with your hands and seeing the direct impact of your work\n\n\nWHAT THIS ROLE IS NOT\n\n - This is not a purely theoretical or design-focused engineering position\n\n - This is not a robotics software or controls engineering role\n\n - This is not limited to repetitive assembly or production-line work\n\n - This is not a position where you'll only follow instructions without opportunities to solve problems\n\nInstead, this role sits at the intersection of robot assembly, hardware integration, testing, and maintenance. You'll be expected to develop a broad understanding of our robotic systems and contribute wherever hands-on technical support is needed.\n\n\nGROWTH & IMPACT\n\nAs we scale our robotic fleet and hardware capabilities, this role will evolve alongside the complexity of our systems and operations.\n\nYou'll have opportunities to develop deeper expertise in robotics, take ownership of increasingly complex technical work, and contribute to improvements in how our robots are assembled, tested, maintained, and supported.\n\nWhether your interests lean toward mechanical systems, electrical integration, troubleshooting, or robotics engineering support, this role offers exposure to a broad range of technical challenges.\n\nIf you enjoy building things, solving problems, and working directly with advanced robotic systems, this is an opportunity to make a tangible impact on how real-world robotics scales.","compensation":{"compensationTierSummary":"$35 – $50 per hour • Offers Equity","scrapeableCompensationSalarySummary":null,"compensationTiers":[{"id":"9afefefa-9d23-4e0c-9e50-47b141302ab6","tierSummary":"$35 – $50 per hour • Offers Equity","title":null,"additionalInformation":null,"components":[{"id":"64ae2bd2-6872-4333-a5a4-747e0c973ffd","summary":"Offers Equity","compensationType":"EquityPercentage","interval":"NONE","currencyCode":null,"minValue":null,"maxValue":null},{"id":"e57107bc-6940-4d25-bef1-df3d5c3ecb09","summary":"$35 – $50 per hour","compensationType":"Salary","interval":"1 HOUR","currencyCode":"USD","minValue":35,"maxValue":50}]}],"summaryComponents":[{"compensationType":"EquityPercentage","interval":"NONE","currencyCode":null,"minValue":null,"maxValue":null},{"compensationType":"Salary","interval":"1 HOUR","currencyCode":"USD","minValue":35,"maxValue":50}]}},{"id":"ab576915-8cbc-4709-a15d-5749ffa42594","title":"Software Engineer: Frontend","department":"Technical Staff","team":"Technical Staff","employmentType":"FullTime","location":"San Francisco Bay Area (San Mateo) or Boston (Somerville)","shouldDisplayCompensationOnJobPostings":false,"secondaryLocations":[],"publishedAt":"2026-10-09T18:49:59.717+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressCountry":"United States"}},"jobUrl":"https://jobs.ashbyhq.com/generalist/ab576915-8cbc-4709-a15d-5749ffa42594","applyUrl":"https://jobs.ashbyhq.com/generalist/ab576915-8cbc-4709-a15d-5749ffa42594/application","descriptionHtml":"At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
We’re looking for a Frontend Engineer to build the interfaces that make advanced robotics intuitive and useful. Your work will help researchers understand model behavior, operators manage robot fleets, and customers build with our foundation model.
You’ll own frontend development from early prototypes to production applications, working closely with design, product, and infrastructure teams. This role combines strong engineering fundamentals with thoughtful product judgment: you should care as much about how an interface feels as how it is built.
What You’ll Do
Build web applications for robot monitoring, data exploration, model training and evaluation, and internal tooling.
Turn complex technical requirements into clear, responsive interfaces that help users make decisions and take action.
Develop interactive visualizations for robot telemetry, video, experiment results, and system health.
Shape frontend architecture that makes complex workflows easy to understand, test, and extend as the product grows.
Establish a cohesive design system across our research platform and robot operator interfaces, with shared components, styles, and interaction patterns.
Work directly with researchers, operators, and customers to understand their workflows, test ideas, and improve the product based on feedback.
Improve the frontend development experience through clear conventions, reusable patterns, and tooling that helps engineers build consistent features quickly.
What You’ll Bring
Experience shipping and maintaining production web applications using TypeScript, React, and modern frontend tooling.
Strong opinions around shared component libraries and UI patterns with good judgment about what to standardize and where flexibility matters.
Strong frontend architecture fundamentals: clear component boundaries, explicit application state, and an ability to simplify complex code and make it easier for others to extend.
Experience managing asynchronous data and user interactions, including keeping interfaces accurate and usable during background updates, slow requests, and failures.
Clear communication and a collaborative approach to working across engineering, design, and product.
Nice to Have
Experience building tools for robotics, AI, scientific computing, or other technically complex domains.
Experience with real-time interfaces, streaming data, or event-driven systems.
Experience keeping data-intensive interfaces fast, including large tables or interactive visualizations and videos.
Experience consolidating UI patterns and incrementally modernizing an existing frontend while continuing to ship product improvements.
Excitement around developing frontend developer tooling, such as component previews or advanced useful end to end or browser tests.
Experience with browser performance profiling, frontend observability, and automated testing.
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs—with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
Applied Scientists own the mastery of new frontier model capabilities. This includes developing post-training recipes for learning a wide range of dexterous tasks — from pushing the frontiers of science lab automation, to generalizing manufacturing and warehouse logistics, to designing open-ended evaluations that challenge what the models can do, and more. You are responsible for hill-climbing broad sets of manipulation capabilities until they are robust, general, and reusable across multiple applications. This role is a hybrid of research, engineering, and operations, and we expect excellence in all three areas.
This is an empirical, model science-first role. You will define what \"good\" looks like for a capability, build the evaluations that measure it, run experiments across model variants and data recipes, analyze the results, and drive the post-training loop. You will leverage post-training, data, task design, and rigorous experimentation, to compound model capabilities: anything mastered for one application can become a strength of the foundation model for entire industries.
Owning end-to-end improvement of target capabilities, from baseline performance to mastery
Designing task suites and evaluation protocols that faithfully capture what research, science partners, and customers need, and that generalize beyond any single deployment
Coordinating data collection, training and fine-tuning models, sweeping data mixtures and configurations, and orchestrating large-scale evaluations
Running rigorous experimental analysis across model variants — isolating variables, quantifying statistical confidence, and diagnosing failure modes from rollout data
Using the stack in new ways rather than redesigning it — and when a capability is fundamentally restricted, you'll work with the pretraining and post-training teams to improve the model
Are comfortable with data analysis at scale: slicing roll out logs, computing metrics, visualizing results, and investigating what happened and why
Care deeply about evaluation, benchmarking, and failure analysis — and are continuously diligent in the face of seemingly repetitive, but subtly changing task evaluations
Enjoy rapid iteration with real-world feedback loops, and are willing to get hands-on with robots and physical task setups when the experiment demands it
Are motivated by making capabilities work for real applications
Can communicate findings clearly to both research teams and partner-facing teams
Have a strong background in machine learning and/or robot learning (e.g. a PhD in a relevant area)