Startups · AI

Member of Technical Staff, Infrastructure

Sieve · San Francisco · On-site

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About Sieve

High-quality video, audio, image, and interaction data for frontier AI. Backed by Y Combinator and AI Grant.

About the role

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.

What they're looking for

  • 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
More about this role

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 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,...

Read the full posting on Sieve's site ↗

Engineering

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