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Sieve

8 open roles indexed with location, benefit, and apply-link signals where available.

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  • Member of Technical Staff, Forward Deployed

    San Francisco | OnSite

    onsite Salary not disclosed

    Member of Technical Staff, Forward Deployed San Francisco | OnSite 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

  • Member of Technical Staff, Infrastructure

    San Francisco | OnSite

    onsite Salary not disclosed

    Member of Technical Staff, Infrastructure San Francisco | OnSite ABOUT US 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 https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/. ABOUT THE ROLE As an infrastructure engineer at Sieve https://www.sievedata.com/, you'll design and engineer systems that handle the compute, scheduling, and orchestration of complex ML + ETL pipelines that need to run quickly, reliably, and cost-effectively on large sums of video. 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. REQUIREMENTS - 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

  • Partnerships & Operations Lead

    San Francisco | OnSite

    onsite Salary not disclosed

    Partnerships & Operations Lead San Francisco | OnSite ABOUT US 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 https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/. ABOUT THE ROLE As Partnerships & 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

  • Member of Technical Staff, Reliability

    San Francisco | OnSite

    onsite Salary not disclosed

    Member of Technical Staff, Reliability San Francisco | OnSite ABOUT US 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. ABOUT THE ROLE 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

  • Member of Technical Staff, Applied Research

    San Francisco | OnSite

    onsite Salary not disclosed

    Member of Technical Staff, Applied Research San Francisco | OnSite ABOUT US 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 https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/. ABOUT THE ROLE As an applied research engineer at Sieve https://www.sievedata.com/, 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. REQUIREMENTS - 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,

  • Research & Product Lead

    San Francisco | OnSite

    onsite Salary not disclosed

    Research & Product Lead San Francisco | OnSite ABOUT US 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 https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/. ABOUT THE ROLE 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

  • Member of Technical Staff

    San Francisco | OnSite

    onsite Salary not disclosed

    Member of Technical Staff San Francisco | OnSite ABOUT US 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 https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/. ABOUT THE ROLE As a software engineer at Sieve https://www.sievedata.com/, 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. REQUIREMENTS - Strong Python developer, experience in Go or Typescript also welcome - Excellent communication

  • Member of Technical Staff, Product

    San Francisco | OnSite

    onsite Salary not disclosed

    Member of Technical Staff, Product San Francisco | OnSite ABOUT US 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. ABOUT THE ROLE 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. WHAT YOU'LL DO - Build and scale a production product used by contributors, partners, and internal teams. - Ship