AI startup building systems for regulated industries, backed by substantial funding.
AI/ML Engineer
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You'll spend mornings translating messy clinical or claims data into something a model can digest, afternoons debugging why a PyTorch pipeline stalls at scale, and Fridays presenting metrics to policy teams who ask harder questions than any reviewer. The work sits at the intersection of prediction and proof — every deployment needs audit trails, drift detection, and the patience to explain confidence intervals to people who've never touched a notebook.
What they're looking for
- 3-10 years shipping ML systems in production, not just experiments
- Fluency in Python and at least one major framework — PyTorch preferred, TensorFlow acceptable
- Demonstrated experience with data pipelines that handle messy, incomplete, or sensitive inputs
- Comfort working with stakeholders in regulated sectors where model interpretability isn't optional
- Willing to be in San Francisco or New York offices part of each week