Autonomize AI is revolutionizing healthcare by streamlining knowledge workflows with AI. We reduce administrative burdens and elevate outcomes, empowering professionals to focus on what truly matters — improving lives.
Requirements
- Working knowledge of modern ML/LLM tooling (Python, PyTorch/TensorFlow, experiment tracking, data/feature stores, eval frameworks, model observability).
- Experience with RAG pipelines, clinical NLP (e.g., de‑identification, coding, entity linking), or payer/provider workflows.
- Background building MLOps platforms or evaluation harnesses for LLMs.
Responsibilities
- Program & Portfolio Leadership: Own the multi‑track plan for ML projects (scoping delivery), including timelines, dependencies, resources, and risk/RAID management.
- Run the operating rhythm: backlog/roadmap, sprint planning, stand‑ups, demos, and executive readouts with crisp status and decision logs.
- Define success criteria and measurable outcomes (quality, latency, cost, safety), then track and improve them.
- Coordinate data pipelines, annotations, experimentation, and evaluation—shipping production‑ready ML with reliability.
- Review designs/PRDs, sanity‑check experiments, and dive into notebooks or dashboards to resolve issues when needed.
- Partner on MLOps best practices (versioning, CI/CD for models, observability, guardrails, rollback plans).
- Establish evaluation frameworks for LLM/RAG and clinical NLP (offline metrics, red‑teaming, human‑in‑the‑loop QA).
Other
- 6+ years in Applied ML/DS/AI (or ML‑heavy product/engineering), including 2+ years leading multi‑workstream ML programs or teams.
- Proven track record shipping ML/LLM systems to production with clear business outcomes.
- Strong program management fundamentals (road‑mapping, risk management, stakeholder alignment) and excellent written/verbal communication.
- Ability to operate in the final mile—closing loops with high judgment, urgency, and attention to detail.
- Healthcare curiosity and comfort with privacy, safety, and compliance considerations.
- Experience mentoring/hiring ML talent and leading vendors/partners.
- A chance to make a real impact in the future of healthcare
- Autonomy, ownership, and the ability to chart your own growth path
- Competitive compensation and benefits
- 100% employer-paid health, vision, and dental insurance
- Retirement plans (401k), disability insurance, employee assistance programs
