Hippocratic AI builds the safest generative AI healthcare agent for health systems, payors, and pharma. Over 180 million clinical interactions across 1,000+ use cases with 60+ partners worldwide. Backed by General Catalyst, Kleiner Perkins and a16z.
About the role
Frontier models are only as good as the data they learn from. At Hippocratic AI, that data decides whether an AI agent safely guides a patient through a medication change at 2 a.m. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 5+ years in technical program management or data operations in an AI/ML or data-intensive environment (3+ years considered for exceptional candidates)
- 2+ years hands-on with data labeling, annotation, or model evaluation, including writing guidelines and managing quality at scale
- Experience sourcing and managing contractor or expert annotator workforces through marketplaces (e.g., Mercor, Upwork, Toloka) or labeling vendors
- Working knowledge of how annotation quality affects model training, including preference data, pairwise comparisons, and rater calibration (RLHF)
- A strong grasp of quality metrics (IAA, precision/recall on gold sets, throughput vs. accuracy tradeoffs)
- A track record of owning critical data or eval projects under time pressure, working with ML engineers and applied scientists, and driving results without direct authority
More about this role
Frontier models are only as good as the data they learn from. At Hippocratic AI, that data decides whether an AI agent safely guides a patient through a medication change at 2 a.m.
Our data powers Polaris, a constellation of models with a 700B-parameter core and specialized safety supervisors. In our evaluations, Polaris reaches 99.95% accuracy on drug-safety benchmarks versus 87.9% for the closest voice-deployable frontier model. The labeling, evals, and rater calibration behind it are how we earn and defend numbers like that.
We’re hiring a Technical Program Manager to run the human-in-the-loop data labeling engine behind our frontier healthcare AI. That spans audio and conversation annotation, clinician-labeled training data, preference and RLHF data, and the evaluations that decide what ships. You’ll work daily with ML researchers, applied scientists, and licensed clinicians. The data you produce feeds directly into our model training and evaluation loops.
Run the data pipelines behind our models. Own end-to-end delivery of labeling and annotation programs, including audio and voice-conversation labeling, supervised labeling, and preference and RLHF data. You’ll manage...
Browse similar: AI jobs · AI startup jobs · Startup jobs · San Francisco Bay Area