Startups · AI

Member of Technical Staff, Machine Learning

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 a Machine Learning Engineer at Sieve, you'll own the entire ML lifecycle — from understanding customer problems, to designing datasets, improving models, building evaluation systems, and shipping production pipelines that deliver measurable improvements in dataset quality.

What they're looking for

  • Strong Python engineer with experience building production ML systems
  • Experience training, fine-tuning, or deploying modern deep learning models
  • Comfortable working with PyTorch and modern foundation models
  • Excellent intuition for evaluation, dataset quality, precision/recall tradeoffs, and edge cases
  • Enjoys rapidly prototyping with new AI models and APIs
  • Comfortable owning projects from customer problem to internal pipelines to deployed solution
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 a Machine Learning Engineer at Sieve, you'll own the entire ML lifecycle — from understanding customer problems, to designing datasets, improving models, building evaluation systems,...

Read the full posting on Sieve's site ↗

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