Distributed Systems Engineer

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 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

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