Member of Technical Staff

7 months ago

Responsibilities

Build AI agent workflows for multi-step clinical reasoning, tool use, and structured decision-making, including guardrails and escalation paths.
Ship AI-powered product features end-to-end from model selection through UX integration.
Improve knowledge bases, search relevance, citation traceability, retrieval accuracy, and data lineage.
Rebuild data ingestion and curation pipelines to support corrections, partner synchronization, traceability, and high-quality training and evaluation datasets.
Build low-latency real-time voice pipelines and voice agents for clinical intake, triage, and follow-up conversations.
Fine-tune voice, video, and foundation models for medical terminology, accents, accessibility, safety, and patient-facing quality.
Build monitoring, analytics, tracing, logging, auditing, and production model-performance tracking.
Design and run training, annotation, evaluation, prompt engineering, RLHF, distillation, and related model-optimization workflows.

Strong programming skills, preferably in Python.
Experience with system refactors, schema migrations, and data infrastructure simplification.
Familiarity with PostgreSQL, including JSONB and vector types, and AWS.
Experience building production systems that power AI or ML workflows.
Hands-on experience with LLM APIs, prompt engineering, and shipping AI-powered product features.
Comfort working across the stack from schema design through production debugging.
Preferred experience with PyTorch, Hugging Face, vLLM, Axolotl, RLHF, DPO, AI agent systems, LLM retrieval systems, real-time voice AI, multimodal models, observability stacks, and containerized deployments.

1-10 employees

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