Job Description
📋 Description Build ML systems that score, validate, and improve complex work products with imperfect labels. Design evaluation frameworks for tasks with partial, delayed, or disputed ground truth. Create feedback loops from review, disagreement, and correction to measurable improvements. Own production ML behavior end-to-end: precision/recall, drift, latency, cost, explainability. Improve model quality with prompting, fine-tuning, retrieval, active learning, and error analysis. Partner with backend engineers to integrate inference into durable, long-running workflows with oversight. 🎯 Requirements Track record shipping ML systems improving product metrics. Strong instincts for model quality, evaluation, and failure modes. Comfort with ambiguous problems and imperfect labels. Judgment on prompting, fine-tuning, retrieval, and human review. Solid fundamentals across the full ML stack. Familiarity with LLM apps or human-in-the-loop ML (plus). 🎁 Benefits Bi-annual performance bonus structure. Generous equity grant vested over 4 years. Up to $15k Relocation bonus. $10K housing bonus (if you live within 0.5 miles of our office). $1.5K monthly stipend for meals. Free Equinox membership.
