Top AI & Machine Learning Jobs in New York City, NY

Own evaluation, measurement, and optimization of production LLM-powered features. Design reproducible evaluation frameworks, run experiments and analyses to identify failure modes and regressions, build metrics and dashboards, partner with engineering to productionize improvements, and mentor teammates on experimental design and measurement best practices.

Design and run evaluations for LLM-powered features: build datasets and rubrics, analyze production logs for failures, run experiments, track product/operational metrics, and partner with engineers to productionize improvements and monitoring dashboards.

Build and ship LLM-powered features across patient and clinical workflows. Partner with clinical operators, prototype AI workflows (prompts, agents, RAG), write Python/SQL to connect AI systems, define success metrics, run evaluations, and iterate based on user feedback.

Embed with clinical and operations teams to identify high-value AI opportunities; build LLM-powered features end-to-end including prompts, orchestration, Python services, evaluation suites, golden datasets, and metrics-driven experiments to measure product impact and prioritize work.

Build and ship LLM-powered production features end-to-end: prompt orchestration, tool calling, retrieval/RAG, embeddings, evaluation infrastructure, observability, safety guardrails, and integrations. Collaborate with clinical teams, prototype quickly, measure outcomes, and raise engineering standards through mentorship and technical leadership.

Build and ship production LLM-powered features across patient-facing products, clinical workflows, and internal tools. Implement AI application layers (prompt orchestration, tool calling, RAG, agent workflows), connect LLMs to internal APIs and systems, and develop evaluation suites and observability for model quality. Prototype rapidly, collaborate with clinical teams, and contribute to AI infrastructure and engineering best practices.