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 12 people. We also raised our Series A earlier this year from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
We process petabytes of video across thousands of nodes and multiple cloud environments. As we scale, reliability, observability, and security become existential.
We’re hiring our first engineer fully dedicated to the infrastructure foundation of Sieve. This is a high-ownership role for someone who thinks deeply about:
throughput and system stability
monitoring and incident response
security and least-privilege design
reducing operational burden for the entire engineering team
You’ll work directly with our CTO and our founding engineers to build the core tooling that powers all of engineering.
This role is for someone who spends their time thinking deeply about reliability, throughput, observability, and security. You’re the kind of engineer who is always anticipating failure modes, eliminating operational risk, and designing systems that don’t break.
If something goes down, you take it personally, and you thrive in that level of responsibility.
Work with engineering to design and validate the infrastructure powering PB-scale workloads
Build and maintain Terraform-managed multi-cloud deployments
Improve cloud and data security (SSO, IAM, least privilege, auditability)
Own incident response and harden systems against failure
Develop CI/CD systems that minimize user error and maximize safety
Build monitoring + alerting platforms (Prometheus, OpenTelemetry, VictoriaMetrics)
Wrap internal reliability tooling with simple UIs for engineers
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
High ownership mindset over critical systems
In-person at our SF HQ
Experience building lightweight internal tooling (APIs, dashboards, Svelte)
Familiarity with object storage systems (“buckets”)
Active GitHub or portfolio projects
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
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 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 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 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 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 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 Video 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
Able to context switch at a moment's notice
Bonus: Experience as an early hire at a startup
Bonus: Active GitHub or portfolio projects
In-person at our SF HQ
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
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 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 an applied research engineer at Sieve, you’ll build high performance building blocks and large scale pipelines to understand video with high precision at internet scale. Often this involves working on ambiguous research problems and finding clever techniques to solve them. You will be working in the computer vision, audio processing, and text processing domains.
You’re likely a good fit if you’re comfortable working with models + APIs and squeezing every drop of performance out of them through clever pre/post-processing, parallelism, pipelining, inference optimization, and occasionally fine-tuning.
2+ years of experience in computer vision or audio processing
Strong Python developer with hands-on experience in PyTorch or similar ML frameworks
Excellent communication skills, especially with customers and external teams
Writes clean, maintainable code—bonus points for active GitHub or portfolio projects
Deep passion for the video domain and media technologies
Motivated by building end-to-end products—not just training models
Able to break problems down from customer level impact to necessary building blocks.
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
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 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 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 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 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 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
About the Role
As a Forward Deployed Engineer at Sieve, you’ll work on highly specific dataset problems for frontier AI labs and build the custom algorithms, models, and pipelines needed to solve them.
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.
The work often spans computer vision, audio processing, text processing, metadata analysis, model adaptation, and quality evaluation. You should be comfortable moving between research prototypes and reliable production pipelines, using models and APIs creatively, and squeezing performance through pre/post-processing, parallelism, inference optimization, fine-tuning, and evaluation loops.
Requirements
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
Benefits
401k + Full Health Insurance
Breakfast, Lunch, and Dinner covered and your choice of snacks
Ubers covered home
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