Sieve is a multi-modal lab curating the world's highest-quality training datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
We partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
Sieve is one of the most capital-efficient teams in AI — roughly 30 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.
As an infrastructure engineer at Sieve, you’ll design and engineer systems that handle the compute, scheduling, and orchestration of complex ML + ETL pipelines that need to run quickly, reliably, and cost-effectively on large sums of video.
You’re likely a good fit if you love optimizing for system uptime, have worked with cloud technologies, optimizing hyper-fast distributed systems at the scale of thousands of GPUs, and building great internal tooling and CI/CD for rapid iteration.
3+ years of experience building foundational data infrastructure
Proficient in working across diverse cloud architectures
Designed and maintained pipelines that process petabytes of data
Developed robust CI/CD pipelines tailored for ML-focused teams
Strong coding experience with Go and Python; Experience with Rust is a plus
Operates as an IC who leads by example
Experience with large-scale video data systems
In-person at our SF HQ
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
*all roles at Sieve require you to be onsite in San Francisco 5 days per week
","descriptionPlain":"ABOUT US\n\nSieve is a multi-modal lab curating the world's highest-quality training datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.\n\n\nWe partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/.\n\n \n\n\nWHY NOW\n\nSieve is one of the most capital-efficient teams in AI — roughly 30 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.\n\n \n\n\nABOUT THE ROLE\n\nAs an infrastructure engineer at Sieve https://www.sievedata.com/, you’ll design and engineer systems that handle the compute, scheduling, and orchestration of complex ML + ETL pipelines that need to run quickly, reliably, and cost-effectively on large sums of video. \n\nYou’re likely a good fit if you love optimizing for system uptime, have worked with cloud technologies, optimizing hyper-fast distributed systems at the scale of thousands of GPUs, and building great internal tooling and CI/CD for rapid iteration. \n\n\n\n\nREQUIREMENTS\n\n - 3+ years of experience building foundational data infrastructure\n\n - Proficient in working across diverse cloud architectures\n\n - Designed and maintained pipelines that process petabytes of data\n\n - Developed robust CI/CD pipelines tailored for ML-focused teams\n\n - Strong coding experience with Go and Python; Experience with Rust is a plus\n\n - Operates as an IC who leads by example\n\n - Experience with large-scale video data systems\n\n - In-person at our SF HQ\n\n\n\n\nBENEFITS\n\n - 401k + Full Health Insurance\n\n - Breakfast, Lunch, and Dinner covered and your choice of snacks\n\n - Ubers covered home\n\n\n\n*all roles at Sieve require you to be onsite in San Francisco 5 days per week"},{"id":"70847a5f-1262-4163-a496-db4db9fdb138","title":"Member of Technical Staff","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2025-09-02T23:55:45.761+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/sieve/70847a5f-1262-4163-a496-db4db9fdb138","applyUrl":"https://jobs.ashbyhq.com/sieve/70847a5f-1262-4163-a496-db4db9fdb138/application","descriptionHtml":"Sieve is a multi-modal lab curating the world's highest-quality training datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
We partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
Sieve is one of the most capital-efficient teams in AI — roughly 30 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.
As a software engineer at Sieve, you'll work across the stack to build and scale the data pipelines that create the datasets we deliver to customers. You'll have ownership over projects end-to-end: from how data is sourced and curated, to developing ML filters, improving system efficiency, and building internal dashboards for QA and delivery. You'll play a critical role in ensuring customers receive high-quality data on time, every time.
This role is ideal for someone who thrives on solving hard problems, enjoys working directly with customers pushing the frontier of multimodal AI, and wants to be challenged to achieve at the highest level.
Strong Python developer, experience in Go or Typescript also welcome
Excellent communication skills, especially with customers and external teams
Writes clean, maintainable code
In-person at our SF HQ
Able to context switch at a moment's notice
Bonus: Experience as an early hire at a startup
Bonus: Active GitHub or portfolio projects
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
*all roles at Sieve require you to be onsite in San Francisco 5 days per week
","descriptionPlain":"ABOUT US\n\nSieve is a multi-modal lab curating the world's highest-quality training datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.\n\n\nWe partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/.\n\n\n\n\nWHY NOW\n\nSieve is one of the most capital-efficient teams in AI — roughly 30 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.\n\n\n\n\nABOUT THE ROLE\n\nAs a software engineer at Sieve, you'll work across the stack to build and scale the data pipelines that create the datasets we deliver to customers. You'll have ownership over projects end-to-end: from how data is sourced and curated, to developing ML filters, improving system efficiency, and building internal dashboards for QA and delivery. You'll play a critical role in ensuring customers receive high-quality data on time, every time.\n\nThis role is ideal for someone who thrives on solving hard problems, enjoys working directly with customers pushing the frontier of multimodal AI, and wants to be challenged to achieve at the highest level.\n\n \n\n\nREQUIREMENTS\n\n - Strong Python developer, experience in Go or Typescript also welcome\n\n - Excellent communication skills, especially with customers and external teams\n\n - Writes clean, maintainable code\n\n - In-person at our SF HQ\n\n - Able to context switch at a moment's notice\n\n - Bonus: Experience as an early hire at a startup\n\n - Bonus: Active GitHub or portfolio projects\n\n\n\n\nBENEFITS\n\n - 401k + Full Health Insurance\n\n - Breakfast, Lunch, and Dinner covered and your choice of snacks\n\n - Ubers covered home\n\n\n\n*all roles at Sieve require you to be onsite in San Francisco 5 days per week"},{"id":"4a0e82d7-a29c-41ef-a48e-6513a7770814","title":"Research & Product Lead","department":"Product","team":"Product","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2025-09-24T18:25:57.598+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/sieve/4a0e82d7-a29c-41ef-a48e-6513a7770814","applyUrl":"https://jobs.ashbyhq.com/sieve/4a0e82d7-a29c-41ef-a48e-6513a7770814/application","descriptionHtml":"Sieve is an AI research lab building the world's highest-quality multimodal datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure, novel multimodal understanding techniques, and dozens of proprietary data sources to develop datasets that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
We've partnered with the world's top AI labs and did $XXM last quarter alone, as a team of just ~25 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
Sieve is one of the most capital-efficient teams in AI — roughly 25 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.
As a Research & Product Lead, you'll be the primary face of Sieve to our customers, top AI labs building frontier models. You'll combine deep technical fluency with strong relationship skills to manage our most important accounts, drive revenue expansion, and translate customer needs into internal priorities. This role sits at the intersection of product, applied research, and customer engagement, and requires someone equally comfortable in a technical deep-dive as they are shaping roadmap priorities or navigating a commercial conversation. Relationships are central to this role. The strongest candidates will already be plugged into the AI lab ecosystem and have trust built with the people and teams we work with.
What You'll Do
Own and grow relationships with Sieve's top AI lab customers end-to-end, from onboarding through expansion
Serve as the technical point of contact, understanding customer data pipelines, model training workflows, and how Sieve's datasets fit into their stack
Translate customer feedback and requirements into clear internal briefs for engineering and data ops
Drive renewals and upsells by identifying new dataset needs and partnership opportunities within existing accounts
Collaborate closely with the partnerships, engineering, and data ops teams to ensure customer deliverables are met on time and at quality
Contribute to sales processes for new customers including demos, technical scoping, and proposal development
Requirements
Strong understanding of ML/AI workflows, particularly around data pipelines and model training
A natural relationship builder with a strong external network, especially across AI labs and frontier model companies
Excellent communication skills, able to translate between engineering and business audiences fluently
Comfortable with ambiguity and moving fast in a startup environment
In-person at our SF HQ
Nice to Have
Existing relationships at AI labs or frontier model companies
Background in video, media, or content-related technologies
Prior startup experience, especially as an early hire
Experience in product, technical operations, or a customer-facing technical role
Benefits
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
Sieve is a multi-modal lab curating the world's highest-quality training datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
We partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
Sieve is one of the most capital-efficient teams in AI — roughly 30 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.
As a Forward Deployed Engineer at Sieve, you’ll work on highly specific dataset problems for frontier AI labs. We're looking for someone with a strong bias to action who likes working closely with customers, untangling messy requirements, and shipping fast.
You’ll work closely with customers and internal teams to understand exactly what data is needed, then turn ambiguous requirements into production systems that can find, generate, filter, transform, evaluate, and package high-quality video datasets at scale.
Comfortable working directly with customers or external teams to translate ambiguous needs into concrete technical systems
Strong Python developer with hands-on experience in PyTorch or similar ML frameworks
Experience building custom algorithms, model workflows, or large-scale data pipelines
Strong intuition for dataset quality, filtering, labeling, evaluation, and edge cases
Able to break customer-level goals down into the models, heuristics, infrastructure, and QA steps needed to deliver
Writes clean, maintainable code and can move quickly without creating brittle systems
Deep passion for video, media technologies, and frontier AI applications
Motivated by delivering end-to-end outcomes, not just training models or writing research code
Bonus: Experience with large-scale video, audio, or multimodal data processing
Bonus: Active contributor to open source projects
Bonus: Experience as an early hire at a startup
In-person at our SF HQ
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
*all roles at Sieve require you to be onsite in San Francisco 5 days per week
","descriptionPlain":"ABOUT US\n\nSieve is a multi-modal lab curating the world's highest-quality training datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.\n\n\nWe partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/.\n\n \n\n\nWHY NOW\n\nSieve is one of the most capital-efficient teams in AI — roughly 30 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.\n\n\n\n\nABOUT THE ROLE\n\nAs a Forward Deployed Engineer at Sieve, you’ll work on highly specific dataset problems for frontier AI labs. We're looking for someone with a strong bias to action who likes working closely with customers, untangling messy requirements, and shipping fast. \n\nYou’ll work closely with customers and internal teams to understand exactly what data is needed, then turn ambiguous requirements into production systems that can find, generate, filter, transform, evaluate, and package high-quality video datasets at scale.\n\n\n\n\nREQUIREMENTS\n\n - Comfortable working directly with customers or external teams to translate ambiguous needs into concrete technical systems\n\n - Strong Python developer with hands-on experience in PyTorch or similar ML frameworks\n\n - Experience building custom algorithms, model workflows, or large-scale data pipelines\n\n - Strong intuition for dataset quality, filtering, labeling, evaluation, and edge cases\n\n - Able to break customer-level goals down into the models, heuristics, infrastructure, and QA steps needed to deliver\n\n - Writes clean, maintainable code and can move quickly without creating brittle systems\n\n - Deep passion for video, media technologies, and frontier AI applications\n\n - Motivated by delivering end-to-end outcomes, not just training models or writing research code\n\n - Bonus: Experience with large-scale video, audio, or multimodal data processing\n\n - Bonus: Active contributor to open source projects\n\n - Bonus: Experience as an early hire at a startup\n\n - In-person at our SF HQ\n\n\n\nBENEFITS\n\n - 401k + Full Health Insurance\n\n - Breakfast, Lunch, and Dinner covered and your choice of snacks\n\n - Ubers covered home\n\n\n\n*all roles at Sieve require you to be onsite in San Francisco 5 days per week"},{"id":"f35923e9-5770-4123-a6a9-c0ba5af66657","title":"Member of Technical Staff, Product","department":"Engineering","team":"Engineering","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-01-27T17:32:17.997+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/sieve/f35923e9-5770-4123-a6a9-c0ba5af66657","applyUrl":"https://jobs.ashbyhq.com/sieve/f35923e9-5770-4123-a6a9-c0ba5af66657/application","descriptionHtml":"Sieve is the only AI research lab exclusively focused on video data. We combine exabyte-scale video infrastructure, novel video understanding techniques, and dozens of data sources to develop datasets that push the frontier of video modeling. Video makes up 80% of internet traffic and has become the enabling digital medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
We’ve partnered with top AI labs and did $XXM last quarter alone, as a team of just 15 people. We also raised our Series A last year from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
As a product engineer at Sieve, you'll help build our video collection platform: a system that pays contributors for submitting video recordings alongside internal product tooling.
You'll work full-stack across frontend, backend, systems, and mobile to ship products quickly, improve reliability, and scale the platform in supporting millions of users. You'll also build internal tools that help the team source, review, and deliver high-quality data efficiently. You'll own projects end-to-end.
This role is ideal for someone who enjoys building products with tight feedback loops, thrives in a high-ownership environment, and wants to work directly on the core engine powering frontier video AI.
Build and scale a production product used by contributors, partners, and internal teams.
Ship full stack features across frontend, backend APIs, and underlying systems.
Ship mobile features that enable easy video capture and submission.
Improve reliability, performance, and developer velocity across the platform.
Build internal tools and workflows that make operations, QA, and delivery fast and consistent.
Work closely with customers and operators to translate needs into product and ship iteratively.
Strong full stack engineer who can take projects from idea to production.
Strong TypeScript + modern frontend experience (React/Next.js preferred).
Mobile experience in React Native, especially for media capture or upload flows.
Backend experience in Python or Go, with solid API and database fundamentals.
Comfort working across product and systems concerns (reliability, performance, observability).
Clear communicator who works well with cross-functional stakeholders.
High ownership and urgency, including willingness to work late nights and weekends when needed.
In-person at our SF HQ
Experience as an early hire at a startup.
History of shipping high-quality products with real users.
Experience building simple tooling, including minimal internal APIs and Svelte dashboards
Active GitHub or portfolio projects.
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
Sieve is a multi-modal lab curating the world's highest-quality training datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
We partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
Sieve is one of the most capital-efficient teams in AI — roughly 30 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.
We process petabytes of video across thousands of nodes and multiple cloud environments, and as we scale, reliability, observability, and security become existential. We're hiring our first engineer fully dedicated to Sieve's infrastructure foundation — a high-ownership role working directly with our CTO and founding engineers to build the core tooling that powers all of engineering. You'll design and validate the infrastructure behind PB-scale workloads, own incident response, harden systems against failure, and build the monitoring, security, and CI/CD tooling the whole team relies on.
This role is ideal for someone who thinks deeply about reliability, throughput, observability, and security — the kind of engineer who anticipates failure modes, eliminates operational risk, and designs systems that don't break. If something goes down, you take it personally, and you thrive in that level of responsibility.
3+ years building internal infrastructure at scale
Experience on-call for Sev 0 / Sev 1 production incidents (L3 preferred)
Strong cloud experience (GCP, AWS, Oracle, Cloudflare, etc.)
Deep Infrastructure-as-Code experience (Terraform preferred)
Familiarity with Argo, Helm, Kustomize, or similar deployment tools
Experience operating observability systems (Prometheus, OTel, VictoriaMetrics)
Backend fundamentals in Python, Go, Rust, or C++
Strong networking + security intuition, including SSO implementation
In-person at our SF HQ
Bonus: Experience building lightweight internal tooling (APIs, dashboards, Svelte)
Bonus: Familiarity with object storage systems (\"buckets\")
Bonus: Active GitHub or portfolio projects
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
*all roles at Sieve require you to be onsite in San Francisco 5 days per week
","descriptionPlain":"ABOUT US\n\nSieve is a multi-modal lab curating the world's highest-quality training datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.\n\n\nWe partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/.\n\n \n\n\nWHY NOW\n\nSieve is one of the most capital-efficient teams in AI — roughly 30 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.\n\n\n\nABOUT THE ROLE\n\nWe process petabytes of video across thousands of nodes and multiple cloud environments, and as we scale, reliability, observability, and security become existential. We're hiring our first engineer fully dedicated to Sieve's infrastructure foundation — a high-ownership role working directly with our CTO and founding engineers to build the core tooling that powers all of engineering. You'll design and validate the infrastructure behind PB-scale workloads, own incident response, harden systems against failure, and build the monitoring, security, and CI/CD tooling the whole team relies on.\n\nThis role is ideal for someone who thinks deeply about reliability, throughput, observability, and security — the kind of engineer who anticipates failure modes, eliminates operational risk, and designs systems that don't break. If something goes down, you take it personally, and you thrive in that level of responsibility.\n\n\n\n\nREQUIREMENTS\n\n - 3+ years building internal infrastructure at scale\n\n - Experience on-call for Sev 0 / Sev 1 production incidents (L3 preferred)\n\n - Strong cloud experience (GCP, AWS, Oracle, Cloudflare, etc.)\n\n - Deep Infrastructure-as-Code experience (Terraform preferred)\n\n - Familiarity with Argo, Helm, Kustomize, or similar deployment tools\n\n - Experience operating observability systems (Prometheus, OTel, VictoriaMetrics)\n\n - Backend fundamentals in Python, Go, Rust, or C++\n\n - Strong networking + security intuition, including SSO implementation\n\n - In-person at our SF HQ\n\n - Bonus: Experience building lightweight internal tooling (APIs, dashboards, Svelte)\n\n - Bonus: Familiarity with object storage systems (\"buckets\")\n\n - Bonus: Active GitHub or portfolio projects\n\n\n\n\nBENEFITS\n\n - 401k + Full Health Insurance\n\n - Breakfast, Lunch, and Dinner covered and your choice of snacks\n\n - Ubers covered home\n\n\n\n*all roles at Sieve require you to be onsite in San Francisco 5 days per week"},{"id":"99792866-ec8b-41b5-bca6-93fc9f397f1d","title":"Product Operations Lead","department":"Product","team":"Product","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-03-11T05:22:44.961+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/sieve/99792866-ec8b-41b5-bca6-93fc9f397f1d","applyUrl":"https://jobs.ashbyhq.com/sieve/99792866-ec8b-41b5-bca6-93fc9f397f1d/application","descriptionHtml":"Sieve is an AI research lab building the world's highest-quality multimodal datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure, novel multimodal understanding techniques, and dozens of proprietary data sources to develop datasets that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
We've partnered with the world's top AI labs and did $XXM last quarter alone, as a team of just ~25 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
Sieve is one of the most capital-efficient teams in AI — roughly 25 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.
As Product Operations Lead, you'll own the day-to-day execution and scaling of Sieve's data operations platform alongside vendor partnerships. This is a deeply operational and semi-technical role. You'll manage our human workforce, build and improve QA processes, handle people sourcing and onboarding, and drive product ops initiatives that make our platform more efficient. A major part of this role is growth: you'll run campaigns and experiments to expand the platform's user base, find new channels for sourcing, and drive adoption. This role is ideal for someone who is both a builder and an optimizer, someone who can get their hands dirty with tooling while also thinking strategically about how to scale a complex operational machine.
What You'll Do
Operate and scale Sieve's internal data ops platform, including workforce management, task assignment, and QA workflows
Drive platform and partnerships growth: run acquisition campaigns, test new sourcing channels, and grow the user base through creative and scalable strategies
Source, onboard, and manage a distributed human workforce for data annotation, curation, and quality review
Build and improve QA processes to ensure data output meets the standards required by frontier AI labs
Own product ops for the data platform. Work with engineering to ship tooling improvements, track operational metrics, and identify gaps
Create documentation, SOPs, and training materials for operational workflows
Requirements
Mixed technical and non-technical skillset, comfortable with data tooling, light scripting, and spreadsheet-level analysis
Strong organizational skills and attention to detail; able to manage multiple concurrent work streams
Growth mindset: experience running or contributing to user acquisition, sourcing campaigns, or platform growth efforts
Bachelor's degree in CS, STEM, or equivalent practical experience
In-person at our SF HQ
Nice to Have
Experience managing human-in-the-loop data operations or annotation pipelines
At least 1 year of engineering experience or strong technical fluency
Experience as an early hire at a startup or spearheading ops at an AI lab
Familiarity with data quality frameworks or ML data pipelines
Benefits
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
Sieve is an AI research lab building the world's highest-quality multimodal datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure, novel multimodal understanding techniques, and dozens of proprietary data sources to develop datasets that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
We've partnered with the world's top AI labs and did $XXM last quarter alone, as a team of just ~25 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
Sieve is one of the most capital-efficient teams in AI — roughly 25 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.
As a Machine Learning Engineer at Sieve, you'll own the entire ML lifecycle — from understanding customer problems, to designing datasets, improving models, building evaluation systems, and shipping production pipelines that deliver measurable improvements in dataset quality.
You'll work directly with frontier AI labs to understand difficult data problems, then build end-to-end systems that solve them. One week you might fine-tune a multimodal model to improve recall on a difficult edge case. The next you might engineer a VLM-based QA pipeline, design a new evaluation framework, or run a large-scale filtering pipeline on millions of hours of multimodal data.
We're looking for engineers who enjoy owning problems end-to-end, from understanding customer requirements through shipping production ML systems that measurably improve dataset quality.
Own model quality for customer-facing video understanding problems
Fine-tune vision-language and multimodal foundation models for specialized tasks
Build automated evaluation and QA pipelines using frontier models like Gemini, GPT, Claude, and open-source VLMs
Design high-precision filtering, ranking, retrieval, and labeling systems over internet-scale video datasets
Create datasets, benchmarks, and evaluation frameworks that continuously improve model quality
Develop production ML pipelines spanning preprocessing, inference, post-processing, and quality validation
Work directly with frontier AI labs to translate ambiguous requirements into scalable ML systems
Ship improvements quickly, measure results, and iterate based on real-world performance
Strong Python engineer with experience building production ML systems
Experience training, fine-tuning, or deploying modern deep learning models
Comfortable working with PyTorch and modern foundation models
Excellent intuition for evaluation, dataset quality, precision/recall tradeoffs, and edge cases
Enjoys rapidly prototyping with new AI models and APIs
Comfortable owning projects from customer problem to internal pipelines to deployed solution
Strong communicator who enjoys working directly with customers and cross-functional teams
Excited by video, multimodal AI, and frontier foundation models
In-person at our SF HQ
*all roles at Sieve require you to be onsite in San Francisco 5 days per week
","descriptionPlain":"ABOUT US\n\nSieve is an AI research lab building the world's highest-quality multimodal datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure, novel multimodal understanding techniques, and dozens of proprietary data sources to develop datasets that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.\n\nWe've partnered with the world's top AI labs and did $XXM last quarter alone, as a team of just ~25 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.\n\n\n\n\nWHY NOW\n\nSieve is one of the most capital-efficient teams in AI — roughly 25 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.\n\n\n\n\nABOUT THE ROLE\n\nAs a Machine Learning Engineer at Sieve, you'll own the entire ML lifecycle — from understanding customer problems, to designing datasets, improving models, building evaluation systems, and shipping production pipelines that deliver measurable improvements in dataset quality.\n\nYou'll work directly with frontier AI labs to understand difficult data problems, then build end-to-end systems that solve them. One week you might fine-tune a multimodal model to improve recall on a difficult edge case. The next you might engineer a VLM-based QA pipeline, design a new evaluation framework, or run a large-scale filtering pipeline on millions of hours of multimodal data.\n\nWe're looking for engineers who enjoy owning problems end-to-end, from understanding customer requirements through shipping production ML systems that measurably improve dataset quality.\n\n\n\n\nWHAT YOU'LL DO\n\n - Own model quality for customer-facing video understanding problems\n\n - Fine-tune vision-language and multimodal foundation models for specialized tasks\n\n - Build automated evaluation and QA pipelines using frontier models like Gemini, GPT, Claude, and open-source VLMs\n\n - Design high-precision filtering, ranking, retrieval, and labeling systems over internet-scale video datasets\n\n - Create datasets, benchmarks, and evaluation frameworks that continuously improve model quality\n\n - Develop production ML pipelines spanning preprocessing, inference, post-processing, and quality validation\n\n - Work directly with frontier AI labs to translate ambiguous requirements into scalable ML systems\n\n - Ship improvements quickly, measure results, and iterate based on real-world performance\n\n\nREQUIREMENTS\n\n - Strong Python engineer with experience building production ML systems\n\n - Experience training, fine-tuning, or deploying modern deep learning models\n\n - Comfortable working with PyTorch and modern foundation models\n\n - Excellent intuition for evaluation, dataset quality, precision/recall tradeoffs, and edge cases\n\n - Enjoys rapidly prototyping with new AI models and APIs\n\n - Comfortable owning projects from customer problem to internal pipelines to deployed solution\n\n - Strong communicator who enjoys working directly with customers and cross-functional teams\n\n - Excited by video, multimodal AI, and frontier foundation models\n\n - In-person at our SF HQ\n\n\n\n*all roles at Sieve require you to be onsite in San Francisco 5 days per week"},{"id":"876eb005-f3ad-47a2-a792-d73c0c1b64d8","title":"Head of Finance","department":"Business Operations","team":"Business Operations","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-07-14T05:21:52.212+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/sieve/876eb005-f3ad-47a2-a792-d73c0c1b64d8","applyUrl":"https://jobs.ashbyhq.com/sieve/876eb005-f3ad-47a2-a792-d73c0c1b64d8/application","descriptionHtml":"Sieve is an AI research lab building the world's highest-quality multimodal datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure, novel multimodal understanding techniques, and dozens of proprietary data sources to develop datasets that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
We've partnered with the world's top AI labs and did $XXM last quarter alone, as a team of just ~25 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
Sieve is one of the most capital-efficient teams in AI — roughly 25 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.
You’ll be Sieve’s first finance leader, owning the financial foundation for our next stage of growth and helping build the finance function from scratch.
This role will own financial planning, infrastructure, and reporting while developing a detailed understanding of Sieve’s unit economics. You’ll help make better decisions across customer deals, compute commitments, contributor payouts, hiring, and capital allocation.
You’ll be equally comfortable building detailed models, working across messy operational datasets, and turning your analysis into clear recommendations.
Build and own Sieve’s financial model, forecasts, budgets, and runway planning
Model the true cost and margin of customer deals across reinforcement learning, computer use, video, and other data types
Partner with leadership on pricing, resource allocation, hiring plans, compute strategy, and other strategic decisions
Model and optimize contributor payouts to balance supply, quality, speed, and margin
Own financial reporting for the leadership team and board
Work across commercial, engineering, and operations teams to improve financial visibility and operating efficiency
Own treasury, monthly close, payroll, tax while helping build the finance team
6+ years of experience in strategic finance, FP&A, investment banking, private equity, or a similarly analytical role
Strong financial modeling skills and a rigorous understanding of unit economics, contribution margin, and cash flow
Built up a tech finance function before, or at least major parts of one, from scratch.
Comfortable operating with significant ownership and ambiguity in a fast-moving startup
Excellent communication skills and experience partnering with senior leadership
Experience working with a modern finance stack + AI tooling
In-person at our SF HQ
Experience at an AI, infrastructure, data, marketplace, or usage-based software company
Experience modeling compute, storage, or other variable infrastructure costs
Experience as an early finance hire at a startup and built teams from scratch
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
Sieve is an AI research lab building the world's highest-quality multimodal datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure, novel multimodal understanding techniques, and dozens of proprietary data sources to develop datasets that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.
We've partnered with the world's top AI labs and did $XXM last quarter alone, as a team of just ~25 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
We're hiring 1–2 Growth Associates to help scale our expert network. Each Associate owns one domain end-to-end: finding experts, getting them on calls, converting them into active contributors, and opening doors to domain-specific firms.
This is a high-volume, high-ownership sourcing role. You'll spend most of your day on LinkedIn and on calls with US-based professionals.
Source experts directly on LinkedIn — identify and reach out to 1000–4000 qualified domain experts per week through personalized, manual outreach
Convert on calls — get qualified prospects on the phone, pitch the opportunity, handle objections, and walk them through onboarding
Own a domain — become fluent in one vertical (e.g., CAD/architecture, VFX/3D, life sciences software), including the tools, job titles, and communities where experts live
Build firm partnerships — secure intros and working relationships with domain-specific firms and studios in the US and existing markets (boutique studios and specialist firms — not BPOs or staffing agencies)
Support marketing and outbound — assist with campaigns and outbound motions for human data collection more broadly
Maintain pipeline hygiene — track every prospect from first touch to activation; report weekly on funnel metrics
100 experts activated per month (completed onboarding + first paid task) — not just signups
15-20 Qualified calls booked per week
30/60-day retention of experts you bring in
Qualified firm intros converted to active partnerships
2–4 years in expert network recruiting (GLG, AlphaSights, etc.), US-facing recruiting/staffing, or B2B SDR work
Excellent spoken and written English; comfortable cold-calling senior US professionals
Willing to work evening IST hours for consistent US timezone overlap
Organized, self-directed, and comfortable being measured on outcomes
Familiarity with any of our target domains (CAD, 3D, VFX, video/audio production, scientific tooling)
Experience with Sales Navigator, Apollo/Clay, or similar outbound tooling