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 combines access to diverse multimodal data, infrastructure to process it at scale, and close relationships with the teams building frontier models. This gives us a unique opportunity to study what makes training data effective—and turn those findings into better models and datasets.
You’ll join a small team building our research capabilities, with ownership over experiments, training systems, and the decisions those results inform.
As a Member of Technical Staff, Applied Research at Sieve, you’ll train and evaluate multimodal models to understand how data shapes their capabilities. Your work will span video generation and audiovisual understanding, connecting advances in data curation with measurable improvements in model performance.
You’ll own the research loop end-to-end: identify a model weakness, form a hypothesis about the data or training approach that could address it, build the experiment, and evaluate the results. This includes fine-tuning and post-training models, developing reproducible training and evaluation pipelines, and running controlled experiments on data quality, composition, and supervision.
You’re likely a good fit if you enjoy moving between research and engineering: reading a paper, implementing a method, debugging a training run, and figuring out whether an apparent improvement holds up. You care about building reliable systems and producing findings that change how we source, curate, and use training data.
What You’ll Work On
Train and post-train models for video generation and multimodal understanding.
Design controlled experiments to measure how data selection, mixtures, and supervision affect model capabilities.
Build evaluations that reveal specific model weaknesses, using quantitative metrics and human judgment.
Develop reliable training infrastructure, including distributed training, efficient data loading, checkpointing, and experiment tracking.
Turn research findings into improvements in our data curation pipelines and products.
Collaborate with research and engineering teams internally and at partner labs to define meaningful problems and communicate results.
2+ years of experience in machine learning research or engineering, with hands-on experience training or fine-tuning deep learning models.
Strong Python and PyTorch skills, including the ability to implement, debug, and modify model training code.
Experience designing experiments, establishing baselines, and evaluating results critically.
Familiarity with modern generative or multimodal architectures, such as diffusion models or transformers.
Comfortable working with large datasets and diagnosing training bottlenecks, instability, and data quality issues.
Able to turn ambiguous research questions into concrete experiments and maintainable systems.
Strong communication skills and the ability to explain findings, tradeoffs, and uncertainty clearly.
Experience training video, image, or audio generation models.
Experience with supervised fine-tuning, preference optimization, or reinforcement learning.
Experience with distributed training and GPU performance optimization.
Research publications, open-source contributions, or substantial independent ML projects.
Experience as an early hire at a startup.
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 combines access to diverse multimodal data, infrastructure to process it at scale, and close relationships with the teams building frontier models. This gives us a unique opportunity to study what makes training data effective—and turn those findings into better models and datasets.\n\nYou’ll join a small team building our research capabilities, with ownership over experiments, training systems, and the decisions those results inform.\n\n\n\n\nABOUT THE ROLE\n\nAs a Member of Technical Staff, Applied Research at Sieve https://www.sievedata.com/, you’ll train and evaluate multimodal models to understand how data shapes their capabilities. Your work will span video generation and audiovisual understanding, connecting advances in data curation with measurable improvements in model performance.\n\nYou’ll own the research loop end-to-end: identify a model weakness, form a hypothesis about the data or training approach that could address it, build the experiment, and evaluate the results. This includes fine-tuning and post-training models, developing reproducible training and evaluation pipelines, and running controlled experiments on data quality, composition, and supervision.\n\nYou’re likely a good fit if you enjoy moving between research and engineering: reading a paper, implementing a method, debugging a training run, and figuring out whether an apparent improvement holds up. You care about building reliable systems and producing findings that change how we source, curate, and use training data.\n\n\n\nWhat You’ll Work On\n\n - Train and post-train models for video generation and multimodal understanding.\n\n - Design controlled experiments to measure how data selection, mixtures, and supervision affect model capabilities.\n\n - Build evaluations that reveal specific model weaknesses, using quantitative metrics and human judgment.\n\n - Develop reliable training infrastructure, including distributed training, efficient data loading, checkpointing, and experiment tracking.\n\n - Turn research findings into improvements in our data curation pipelines and products.\n\n - Collaborate with research and engineering teams internally and at partner labs to define meaningful problems and communicate results.\n\n\n\n\nREQUIREMENTS\n\n - 2+ years of experience in machine learning research or engineering, with hands-on experience training or fine-tuning deep learning models.\n\n - Strong Python and PyTorch skills, including the ability to implement, debug, and modify model training code.\n\n - Experience designing experiments, establishing baselines, and evaluating results critically.\n\n - Familiarity with modern generative or multimodal architectures, such as diffusion models or transformers.\n\n - Comfortable working with large datasets and diagnosing training bottlenecks, instability, and data quality issues.\n\n - Able to turn ambiguous research questions into concrete experiments and maintainable systems.\n\n - Strong communication skills and the ability to explain findings, tradeoffs, and uncertainty clearly.\n \n \n\n\nBONUS\n\n - Experience training video, image, or audio generation models.\n\n - Experience with supervised fine-tuning, preference optimization, or reinforcement learning.\n\n - Experience with distributed training and GPU performance optimization.\n\n - Research publications, open-source contributions, or substantial independent ML projects.\n\n - Experience as an early hire at a startup.\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 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 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 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 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 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 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 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 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 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 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":"7928c223-1fde-4b2b-bffe-a29ffda17533","title":"Growth Associate","department":"Business Operations","team":"Business Operations","employmentType":"FullTime","location":"India","secondaryLocations":[],"publishedAt":"2026-07-28T02:58:00.039+00:00","isListed":true,"isRemote":true,"workplaceType":"Remote","address":null,"jobUrl":"https://jobs.ashbyhq.com/sieve/7928c223-1fde-4b2b-bffe-a29ffda17533","applyUrl":"https://jobs.ashbyhq.com/sieve/7928c223-1fde-4b2b-bffe-a29ffda17533/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.
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
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 the first business development person, you'll build and deepen relationships across frontier AI labs, emerging model companies, and the broader data ecosystem. You'll identify new labs to work with, develop relationships with additional groups inside existing customers, and recognize emerging opportunities where Sieve can help.
You'll report directly to the CEO and work closely with our GMs and COO. Your job is to find the right people, create high-value conversations, shape opportunities early, and pull the right internal and external levers to help them progress. Our GMs will own commercial scoping, pricing, and closing.
You'll also own the near-term strategy and execution for programs that create inbound demand, including events, conferences, ecosystem partnerships, and marketing initiatives.
Build trusted relationships with researchers, data leaders, product teams, and executives at frontier AI labs and emerging model companies
Identify and engage new labs while opening relationships with additional teams and buying centers inside existing customers
Map the organizations that matter: understand who is working on which models, modalities, capabilities, and data problems
Stay close to changes in model training, post-training, evaluations, RL environments, and multimodal research to recognize where new data needs are emerging
Develop clear opportunity theses that connect a lab's research priorities or model limitations to Sieve's data and infrastructure capabilities
Create and facilitate high-value conversations between external stakeholders and the appropriate Sieve GM
Prepare internal teams with the context they need, including stakeholder maps, research priorities, customer needs, relevant Sieve capabilities, and recommended next steps
Remain involved after the initial introduction, using relationships, follow-ups, references, events, executive engagement, and other strategic levers to help opportunities progress
Work with the CEO, GMs, and COO to prioritize the relationships and opportunities that matter most
Own the strategy and execution for selective programs that generate inbound demand, including executive dinners, research events, conference presence, ecosystem partnerships, content, and other creative initiatives
Represent Sieve at industry events and in the communities where AI researchers, data leaders, founders, and investors spend time
Build a strong view of the AI data market, including emerging customer needs, competitor activity, organizational changes at labs, and new categories Sieve should pursue
Maintain a clear, lightweight system for tracking important relationships, active opportunities, and next steps
Deep familiarity with the frontier AI lab and AI data ecosystem, with an existing network or demonstrated ability to build trusted relationships within it
Experience in strategic business development, partnerships, investing, company-building, or another relationship-driven role in AI
Strong understanding of how foundation models are trained and improved, including the role of pretraining, post-training, evaluations, human data, multimodal data, and RL environments
The technical judgment to understand what makes data useful for training and to hold credible conversations with AI researchers and technical leaders
Exceptional relationship-building skills and the judgment to know which people, organizations, and opportunities matter
Ability to communicate fluently with researchers, founders, executives, operators, and commercial stakeholders
High agency and comfort personally executing across relationship development, events, marketing, and other zero-to-one initiatives
Strong organizational judgment and the ability to manage many long-term relationships
In-person at our San Francisco HQ
Experience at a human-data, training-data, evaluation, or AI infrastructure company
Direct experience scoping or executing data engagements with frontier AI labs
Previous experience working at a frontier lab, founding an AI company, or investing in the AI and data ecosystem
Existing relationships across research, data, post-training, evaluations, procurement, and executive teams at major AI labs
Experience with multimodal data, reinforcement learning environments, human feedback, red teaming, or model evaluations
Experience building executive events, ecosystem programs, strategic content, or other inbound-demand initiatives from scratch
Technical or research experience beyond the level required to sell or manage partnerships
401(k) and full health insurance
Breakfast, lunch, and dinner covered, plus your choice of snacks
Ubers covered home
*all roles at Sieve require you to be onsite in San Francisco 5 days per week
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. We're growing fast, and the systems, processes, and functions that got us here won't be the ones that get us to the next stage. You'll join at the point where you can have outsized leverage: close enough to leadership to shape decisions, hands-on enough to build the functions that don't exist yet.
As part of our Business Operations team , you'll work directly with our executive team to translate strategic priorities into operational reality. This isn't a scheduling or note-taking role, you'll own ambiguous, cross-functional problems end-to-end, stand up new functions from scratch, and bring rigor to how the company operates as it scales.
Work directly with leadership team to identify, prioritize, and drive the company's strategic initiatives
Build and own new operational functions as the company scales — from planning and reporting processes to systems for finance, people, and GTM operations that don't yet exist
Drive cross-functional projects from ambiguity to execution, working directly with engineering, GTM, and finance to unblock progress and hold owners accountable to deadlines
Help run the operating cadence of the company: goal-setting, weekly/monthly business reviews, and org-wide planning
Get into the technical details where needed — jumping in to support different verticals
Identify gaps in how the company operates before they become urgent, and build the lightweight systems and processes to close them
Support hiring across the company as we scale the team
2-5 years of experience in a high-ownership, cross-functional role; chief of staff, business operations, strategy & operations, management consulting, or founding a company
Experience at a hyper-growth startup, ideally one that scaled quickly and required building new functions and processes from scratch
Some technical fluency — comfortable having technical conversation, especially in the multi-modal data space, understanding basic infrastructure or model training concepts, or working directly with engineers, even if you're not an engineer yourself
Strong business operational instincts: comfort with financial models, dashboards, and translating ambiguous goals into concrete plans
High agency and a bias toward action. You should be comfortable picking up unfamiliar problems and driving them to resolution without much guidance
Strong organizational skills and the ability to manage multiple concurrent work-streams without dropping details
Experience building out a specific function (finance, people ops, GTM ops)
A technical background (CS, engineering, or a related field) even if your career has moved into operations or strategy
401(k) and full health insurance
Breakfast, lunch, and dinner covered, plus 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\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, 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 30 people serving the world's leading AI labs across every major data modality. We're growing fast, and the systems, processes, and functions that got us here won't be the ones that get us to the next stage. You'll join at the point where you can have outsized leverage: close enough to leadership to shape decisions, hands-on enough to build the functions that don't exist yet.\n\n\n\n\nABOUT THE ROLE\n\nAs part of our Business Operations team , you'll work directly with our executive team to translate strategic priorities into operational reality. This isn't a scheduling or note-taking role, you'll own ambiguous, cross-functional problems end-to-end, stand up new functions from scratch, and bring rigor to how the company operates as it scales.\n\n\n\n\nWHAT YOU'LL DO\n\n - Work directly with leadership team to identify, prioritize, and drive the company's strategic initiatives\n\n - Build and own new operational functions as the company scales — from planning and reporting processes to systems for finance, people, and GTM operations that don't yet exist\n\n - Drive cross-functional projects from ambiguity to execution, working directly with engineering, GTM, and finance to unblock progress and hold owners accountable to deadlines\n\n - Help run the operating cadence of the company: goal-setting, weekly/monthly business reviews, and org-wide planning\n\n - Get into the technical details where needed — jumping in to support different verticals\n\n - Identify gaps in how the company operates before they become urgent, and build the lightweight systems and processes to close them\n\n - Support hiring across the company as we scale the team\n \n \n\n\nREQUIREMENTS\n\n - 2-5 years of experience in a high-ownership, cross-functional role; chief of staff, business operations, strategy & operations, management consulting, or founding a company\n\n - Experience at a hyper-growth startup, ideally one that scaled quickly and required building new functions and processes from scratch\n\n - Some technical fluency — comfortable having technical conversation, especially in the multi-modal data space, understanding basic infrastructure or model training concepts, or working directly with engineers, even if you're not an engineer yourself\n\n - Strong business operational instincts: comfort with financial models, dashboards, and translating ambiguous goals into concrete plans\n\n - High agency and a bias toward action. You should be comfortable picking up unfamiliar problems and driving them to resolution without much guidance\n\n - Strong organizational skills and the ability to manage multiple concurrent work-streams without dropping details\n \n \n\n\nNICE TO HAVE\n\n - Experience building out a specific function (finance, people ops, GTM ops)\n\n - A technical background (CS, engineering, or a related field) even if your career has moved into operations or strategy\n \n \n\n\nBENEFITS\n\n - 401(k) and full health insurance\n\n - Breakfast, lunch, and dinner covered, plus your choice of snacks\n\n - Ubers covered home\n\n*All roles at Sieve require you to be onsite in San Francisco 5 days per week"},{"id":"91af747a-2f9e-4eff-a03a-be0447e9594a","title":"Growth Operations Lead","department":"Product","team":"Product","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-09-16T06:50:29.116+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/sieve/91af747a-2f9e-4eff-a03a-be0447e9594a","applyUrl":"https://jobs.ashbyhq.com/sieve/91af747a-2f9e-4eff-a03a-be0447e9594a/application","descriptionHtml":"Sieve is a multimodal lab curating the world’s highest-quality training datasets, spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure with novel multimodal understanding techniques to push the frontier of foundation models. We exist to solve one of the biggest bottlenecks in AI: high-quality training data.
We partner with top AI labs and did $XXM last quarter alone, with a team of roughly 30 people. We raised our Series A from firms including Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
AI’s next wave needs data from people with real skills, creative expertise, and access to the physical world. Building a contributor network that can meet that demand is central to Sieve’s growth.
You’ll join early enough to build the systems that shape how contributors discover Sieve, start earning, and keep coming back. Your work will directly expand the data available to the world’s leading AI labs.
We’re hiring a Growth Operations Lead to build and own growth for our contributor platform. You’ll run experiments to acquire contributors, improve activation and retention, and develop supply-side partnerships across physical AI and media generation.
This is a hands-on role for someone who can build from scratch. You’ll find creative ways to reach contributors, test what works, and turn successful experiments into repeatable systems. You should be equally comfortable launching a campaign, digging into funnel data, improving onboarding, and pitching a potential partner.
Run growth experiments: Develop and test acquisition channels across outbound, referrals, communities, content, paid campaigns, and unconventional growth tactics.
Build growth systems from scratch: Create the tooling, automation, tracking, and playbooks that turn successful experiments into repeatable contributor acquisition.
Improve activation and retention: Identify where contributors drop off, shorten the path to a first paid task, and build programs that keep them engaged and contributing.
Develop supply-side partnerships: Source, pitch, and launch partnerships with studios, creator networks, specialist firms, and organizations that can bring contributors and data into Sieve.
Expand supply across physical AI and media generation: Translate emerging project needs into targeted campaigns and partnerships that bring in the right skills, access, and expertise.
Own growth measurement: Track acquisition cost, conversion, activation, retention, and contribution quality; use the results to decide what to scale or stop.
Work across product and operations: Turn contributor feedback and experiment results into improvements to onboarding, communication, incentives, and the platform experience.
Consistent growth in qualified, active contributors who complete paid tasks
Higher conversion from signup to first paid task and a shorter time to activation
Stronger 30/60/90-day retention and repeat participation
Multiple repeatable acquisition channels with measurable costs and results
Active partnerships that deliver relevant contributors and usable data
Growth systems that support increasing volume while maintaining contributor quality
Experience owning growth, growth operations, or marketplace supply, with a track record of building programs from scratch
Demonstrated ability to design experiments, launch quickly, measure results, and scale what works
Strong analytical skills; comfortable working with funnel data, cohorts, dashboards, and acquisition economics
Hands-on experience with outbound tools, CRMs, lifecycle messaging, and workflow automation
Strong communication and commercial instincts; comfortable recruiting early contributors and closing partnerships yourself
Resourceful, self-directed, and willing to handle the operational details needed to get a new initiative off the ground
Based in San Francisco or willing to relocate
Experience growing the supply side of a marketplace, contributor platform, creator network, or expert community
Familiarity with physical AI, robotics, media generation, or AI training data
Experience building referral programs, contributor communities, or retention campaigns
Existing relationships with creative studios, professional communities, or organizations relevant to data collection
Ability to use SQL, scripting, or AI tools to analyze data and build lightweight internal tools
401(k) and full health insurance
Breakfast, lunch, and dinner covered, plus 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 multimodal lab curating the world’s highest-quality training datasets, spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure with novel multimodal understanding techniques to push the frontier of foundation models. We exist to solve one of the biggest bottlenecks in AI: high-quality training data.\n\nWe partner with top AI labs and did $XXM last quarter alone, with a team of roughly 30 people. We raised our Series A from firms including 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\nWHY NOW\n\nAI’s next wave needs data from people with real skills, creative expertise, and access to the physical world. Building a contributor network that can meet that demand is central to Sieve’s growth.\n\nYou’ll join early enough to build the systems that shape how contributors discover Sieve, start earning, and keep coming back. Your work will directly expand the data available to the world’s leading AI labs.\n\n\n\nABOUT THE ROLE\n\nWe’re hiring a Growth Operations Lead to build and own growth for our contributor platform. You’ll run experiments to acquire contributors, improve activation and retention, and develop supply-side partnerships across physical AI and media generation.\n\nThis is a hands-on role for someone who can build from scratch. You’ll find creative ways to reach contributors, test what works, and turn successful experiments into repeatable systems. You should be equally comfortable launching a campaign, digging into funnel data, improving onboarding, and pitching a potential partner.\n\n\n\nWHAT YOU’LL DO\n\n - Run growth experiments: Develop and test acquisition channels across outbound, referrals, communities, content, paid campaigns, and unconventional growth tactics.\n\n - Build growth systems from scratch: Create the tooling, automation, tracking, and playbooks that turn successful experiments into repeatable contributor acquisition.\n\n - Improve activation and retention: Identify where contributors drop off, shorten the path to a first paid task, and build programs that keep them engaged and contributing.\n\n - Develop supply-side partnerships: Source, pitch, and launch partnerships with studios, creator networks, specialist firms, and organizations that can bring contributors and data into Sieve.\n\n - Expand supply across physical AI and media generation: Translate emerging project needs into targeted campaigns and partnerships that bring in the right skills, access, and expertise.\n\n - Own growth measurement: Track acquisition cost, conversion, activation, retention, and contribution quality; use the results to decide what to scale or stop.\n\n - Work across product and operations: Turn contributor feedback and experiment results into improvements to onboarding, communication, incentives, and the platform experience.\n \n \n\n\nWHAT SUCCESS LOOKS LIKE\n\n - Consistent growth in qualified, active contributors who complete paid tasks\n\n - Higher conversion from signup to first paid task and a shorter time to activation\n\n - Stronger 30/60/90-day retention and repeat participation\n\n - Multiple repeatable acquisition channels with measurable costs and results\n\n - Active partnerships that deliver relevant contributors and usable data\n\n - Growth systems that support increasing volume while maintaining contributor quality\n\n\n\n\nREQUIREMENTS\n\n - Experience owning growth, growth operations, or marketplace supply, with a track record of building programs from scratch\n\n - Demonstrated ability to design experiments, launch quickly, measure results, and scale what works\n\n - Strong analytical skills; comfortable working with funnel data, cohorts, dashboards, and acquisition economics\n\n - Hands-on experience with outbound tools, CRMs, lifecycle messaging, and workflow automation\n\n - Strong communication and commercial instincts; comfortable recruiting early contributors and closing partnerships yourself\n\n - Resourceful, self-directed, and willing to handle the operational details needed to get a new initiative off the ground\n\n - Based in San Francisco or willing to relocate\n\n\n\n\nNICE TO HAVE\n\n - Experience growing the supply side of a marketplace, contributor platform, creator network, or expert community\n\n - Familiarity with physical AI, robotics, media generation, or AI training data\n\n - Experience building referral programs, contributor communities, or retention campaigns\n\n - Existing relationships with creative studios, professional communities, or organizations relevant to data collection\n\n - Ability to use SQL, scripting, or AI tools to analyze data and build lightweight internal tools\n \n \n\n\nBENEFITS\n\n - 401(k) and full health insurance\n\n - Breakfast, lunch, and dinner covered, plus your choice of snacks\n\n - Ubers covered home\n\n*All roles at Sieve require you to be onsite in San Francisco 5 days per week"},{"id":"025b0b10-6072-41ab-bcad-6fb4774b973b","title":"International Field Operations Lead","department":"Product","team":"Product","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-10-05T15:12:37.185+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/sieve/025b0b10-6072-41ab-bcad-6fb4774b973b","applyUrl":"https://jobs.ashbyhq.com/sieve/025b0b10-6072-41ab-bcad-6fb4774b973b/application","descriptionHtml":"Sieve is a multimodal lab curating the world’s highest-quality training datasets, spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure with novel multimodal understanding techniques to push the frontier of foundation models. We exist to solve one of the biggest bottlenecks in AI: high-quality training data.
We partner with top AI labs and did $XXM last quarter alone, with a team of roughly 40 people. We raised our Series A from firms including Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
We’re standing up data operations internationally — recording footage, hiring people on the ground, and building the local capacity those programs need. That work won’t scale from SF alone. We need someone who’s done on-the-ground ops and can expand teams internationally without waiting for a perfect playbook.
We’re hiring an International Field Operations Lead to help build and expand Sieve’s on-the-ground operations abroad. You’ll help set up local collection (including recording footage), hire and manage people in-market, and turn early international efforts into reliable operating systems.
This is a hands-on ops role for someone with direct field experience — not a remote-only coordinator. You’ll travel when needed, solve problems in the moment, and build the teams and processes that make international data collection repeatable.
Stand up international ops: Help launch and expand on-the-ground operations in priority markets, including footage recording and related collection workflows.
Hire and grow local teams: Source, hire, onboard, and manage people in-market; build the staffing model as volume grows.
Own day-to-day field execution: Solve logistics, quality, scheduling, and vendor/partner issues so collection stays on track.
Build repeatable playbooks: Turn one-off market launches into documented processes for hiring, training, quality control, and escalation.
Partner with SF product and ops: Translate project requirements into field plans; feed back what’s working and what breaks in-market.
Scale carefully: Balance speed with quality, compliance, and contributor/operator experience as we expand.
Live international ops that reliably deliver footage and other required data
Local teams hired, trained, and producing without constant firefighting from SF
Clear playbooks for launching and expanding into new markets
Improving quality, throughput, and time-to-launch across sites
Strong coordination between field teams and SF stakeholders
Direct on-the-ground operations experience, ideally expanding teams internationally
Track record hiring and managing people in the field (contractors, vendors, or full-time)
Comfort with ambiguity, travel, and building systems where none exist yet
Strong operator instincts: logistics, quality, people management, and follow-through
Clear communicator across time zones and cultures
Based in San Francisco or willing to relocate; able to travel internationally as needed
Experience in data collection, media production, field research, marketplace ops, or logistics in emerging markets
Prior work standing up ops in multiple countries
Familiarity with physical AI, robotics, or AI training data workflows
Language skills relevant to priority markets
401(k) and full health insurance
Breakfast, lunch, and dinner covered, plus 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 multimodal lab curating the world’s highest-quality training datasets, spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure with novel multimodal understanding techniques to push the frontier of foundation models. We exist to solve one of the biggest bottlenecks in AI: high-quality training data.\n\nWe partner with top AI labs and did $XXM last quarter alone, with a team of roughly 40 people. We raised our Series A from firms including Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.\n\n\n\n\nWHY NOW\n\nWe’re standing up data operations internationally — recording footage, hiring people on the ground, and building the local capacity those programs need. That work won’t scale from SF alone. We need someone who’s done on-the-ground ops and can expand teams internationally without waiting for a perfect playbook.\n\n\n\n\nABOUT THE ROLE\n\nWe’re hiring an International Field Operations Lead to help build and expand Sieve’s on-the-ground operations abroad. You’ll help set up local collection (including recording footage), hire and manage people in-market, and turn early international efforts into reliable operating systems.\n\nThis is a hands-on ops role for someone with direct field experience — not a remote-only coordinator. You’ll travel when needed, solve problems in the moment, and build the teams and processes that make international data collection repeatable.\n\n\n\n\nWHAT YOU’LL DO\n\n - Stand up international ops: Help launch and expand on-the-ground operations in priority markets, including footage recording and related collection workflows.\n\n - Hire and grow local teams: Source, hire, onboard, and manage people in-market; build the staffing model as volume grows.\n\n - Own day-to-day field execution: Solve logistics, quality, scheduling, and vendor/partner issues so collection stays on track.\n\n - Build repeatable playbooks: Turn one-off market launches into documented processes for hiring, training, quality control, and escalation.\n\n - Partner with SF product and ops: Translate project requirements into field plans; feed back what’s working and what breaks in-market.\n\n - Scale carefully: Balance speed with quality, compliance, and contributor/operator experience as we expand.\n\n\nWHAT SUCCESS LOOKS LIKE\n\n - Live international ops that reliably deliver footage and other required data\n\n - Local teams hired, trained, and producing without constant firefighting from SF\n\n - Clear playbooks for launching and expanding into new markets\n\n - Improving quality, throughput, and time-to-launch across sites\n\n - Strong coordination between field teams and SF stakeholders\n\n\nREQUIREMENTS\n\n - Direct on-the-ground operations experience, ideally expanding teams internationally\n\n - Track record hiring and managing people in the field (contractors, vendors, or full-time)\n\n - Comfort with ambiguity, travel, and building systems where none exist yet\n\n - Strong operator instincts: logistics, quality, people management, and follow-through\n\n - Clear communicator across time zones and cultures\n\n - Based in San Francisco or willing to relocate; able to travel internationally as needed\n\n\nNICE TO HAVE\n\n - Experience in data collection, media production, field research, marketplace ops, or logistics in emerging markets\n\n - Prior work standing up ops in multiple countries\n\n - Familiarity with physical AI, robotics, or AI training data workflows\n\n - Language skills relevant to priority markets\n\n\nBENEFITS\n\n - 401(k) and full health insurance\n\n - Breakfast, lunch, and dinner covered, plus 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":"b4947fec-dcf6-4f37-8641-60de801f1230","title":"Strategic Partnerships & Ops Lead, Physical AI","department":"Product","team":"Product","employmentType":"FullTime","location":"San Francisco","secondaryLocations":[],"publishedAt":"2026-10-05T15:09:03.813+00:00","isListed":true,"isRemote":false,"workplaceType":"OnSite","address":{"postalAddress":{"addressRegion":"California","addressCountry":"United States","addressLocality":"San Francisco"}},"jobUrl":"https://jobs.ashbyhq.com/sieve/b4947fec-dcf6-4f37-8641-60de801f1230","applyUrl":"https://jobs.ashbyhq.com/sieve/b4947fec-dcf6-4f37-8641-60de801f1230/application","descriptionHtml":"Sieve is a multimodal lab curating the world’s highest-quality training datasets, spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure with novel multimodal understanding techniques to push the frontier of foundation models. We exist to solve one of the biggest bottlenecks in AI: high-quality training data.
We partner with top AI labs and did $XXM last quarter alone, with a team of roughly 40 people. We raised our Series A from firms including Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
Physical AI needs data from real industrial environments — factories, manufacturing lines, and operations that don’t show up on the open web. Unlocking that access, and running the ops that turn it into lab-grade data, is a core growth constraint. You’ll join early enough to build both the partnerships and the operating system behind them.
This role mixes industrial partnerships with hands-on data ops. You’ll open doors into factories and similar environments, then run the workforce, QA, and platform work that turns that access into reliable multimodal data for frontier labs.
Strong fits look like industrials consultants, robotics operators, PE ops folks, or early ops hires who’ve already managed human-in-the-loop work and know how to earn trust with plant leaders and ops teams.
Open industrial access: Identify, pitch, and close partnerships with factories, manufacturers, and industrial operators; navigate security and compliance from first intro through live collection.
Operate the data ops platform: Run workforce management, task assignment, and QA workflows; build SOPs and training so quality stays at the bar frontier labs require.
Grow supply and partnerships: Source, onboard, and manage a distributed workforce for annotation, curation, and review; test acquisition and sourcing channels that scale.
Own product ops with engineering: Ship tooling improvements, track operational metrics, and close gaps in the data platform.
Turn one-offs into systems: Document playbooks so partner wins and ops workflows repeat across sites and programs.
Direct relationships into factories, manufacturing, or adjacent industrial environments — or a clear track record of building them
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
Comfort with ambiguous, relationship-heavy work and the unglamorous ops needed to make a partnership live
Bachelor’s in CS, STEM, or equivalent practical experience; in-person at our SF HQ
Experience managing human-in-the-loop data operations or annotation pipelines
At least 1 year of engineering experience or strong technical fluency
Prior work inside manufacturing, robotics deployment, factory ops, PE portfolio ops, or as an early hire / AI-lab ops lead
Familiarity with data quality frameworks, ML data pipelines, or physical AI
401(k) and full health insurance
Breakfast, lunch, and dinner covered, plus 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 multimodal lab curating the world’s highest-quality training datasets, spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure with novel multimodal understanding techniques to push the frontier of foundation models. We exist to solve one of the biggest bottlenecks in AI: high-quality training data.\n\nWe partner with top AI labs and did $XXM last quarter alone, with a team of roughly 40 people. We raised our Series A from firms including Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.\n\n\n\n\nWHY NOW\n\nPhysical AI needs data from real industrial environments — factories, manufacturing lines, and operations that don’t show up on the open web. Unlocking that access, and running the ops that turn it into lab-grade data, is a core growth constraint. You’ll join early enough to build both the partnerships and the operating system behind them.\n\n\n\n\nABOUT THE ROLE\n\nThis role mixes industrial partnerships with hands-on data ops. You’ll open doors into factories and similar environments, then run the workforce, QA, and platform work that turns that access into reliable multimodal data for frontier labs.\n\nStrong fits look like industrials consultants, robotics operators, PE ops folks, or early ops hires who’ve already managed human-in-the-loop work and know how to earn trust with plant leaders and ops teams.\n\n\n\n\nWHAT YOU’LL DO\n\n - Open industrial access: Identify, pitch, and close partnerships with factories, manufacturers, and industrial operators; navigate security and compliance from first intro through live collection.\n\n - Operate the data ops platform: Run workforce management, task assignment, and QA workflows; build SOPs and training so quality stays at the bar frontier labs require.\n\n - Grow supply and partnerships: Source, onboard, and manage a distributed workforce for annotation, curation, and review; test acquisition and sourcing channels that scale.\n\n - Own product ops with engineering: Ship tooling improvements, track operational metrics, and close gaps in the data platform.\n\n - Turn one-offs into systems: Document playbooks so partner wins and ops workflows repeat across sites and programs.\n\n\nREQUIREMENTS\n\n - Direct relationships into factories, manufacturing, or adjacent industrial environments — or a clear track record of building them\n\n - Mixed technical and non-technical skillset; comfortable with data tooling, light scripting, and spreadsheet-level analysis\n\n - Strong organizational skills and attention to detail; able to manage multiple concurrent work streams\n\n - Growth mindset: experience running or contributing to user acquisition, sourcing campaigns, or platform growth\n\n - Comfort with ambiguous, relationship-heavy work and the unglamorous ops needed to make a partnership live\n\n - Bachelor’s in CS, STEM, or equivalent practical experience; in-person at our SF HQ\n\n\nNICE TO HAVE\n\n - Experience managing human-in-the-loop data operations or annotation pipelines\n\n - At least 1 year of engineering experience or strong technical fluency\n\n - Prior work inside manufacturing, robotics deployment, factory ops, PE portfolio ops, or as an early hire / AI-lab ops lead\n\n - Familiarity with data quality frameworks, ML data pipelines, or physical AI\n\n\nBENEFITS\n\n - 401(k) and full health insurance\n\n - Breakfast, lunch, and dinner covered, plus 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"}],"apiVersion":"1"}