Source description
About the role
About US
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 https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/.
WHY NOW
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.
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
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3+ years of experience building foundational data infrastructure
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Proficient in working across diverse cloud architectures
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Designed and maintained pipelines that process petabytes of data
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Developed robust CI/CD pipelines tailored for ML-focused teams
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Strong coding experience with Go and Python; Experience with Rust is a plus
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Operates as an IC who leads by example
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Experience with large-scale video data systems
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In-person at our SF HQ
Benefits
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401k + Full Health Insurance
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Breakfast, Lunch, and Dinner covered and your choice of snacks
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Ubers covered home
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*all roles at Sieve require you to be onsite in San Francisco 5 days per week
More at Sieve
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