Sieve is the only AI research lab exclusively focused on video data.

Video already makes up 80% of internet traffic and has become the dominant medium driving creativity, communication, gaming, AR/VR, and robotics. Unlocking the ability to truly model video is the key to breakthroughs across all of these domains but progress has been bottlenecked by one thing: high-quality training data. That’s where Sieve comes in.

We bring together exabyte-scale video infrastructure, novel video understanding techniques, and dozens of diverse data sources to create datasets that push the frontier of video modeling. This unique combination allows us to deliver data with unmatched precision, quality, and speed which has earned the trust of frontier AI labs, Fortune 100 companies, and fast-growing generative AI startups.

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.

Sieve scaled from 0 to $XXM in revenue in the second half of 2025, with a relatively small team of 12 people. We also recently raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.

About the Role

As a distributed systems 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.

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 Go and Python

• Operates as an IC who leads by example

• Experience with large-scale video data systems

• In-person at our SF HQ