About Autonomize AI
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. We're growing fast and looking for bold, driven teammates to join us.
The Opportunity
We’re hiring an Applied ML Manager to program‑manage a portfolio of ML initiatives—from LLM/RAG workflows to clinical NLP and MLOps. You’ll create clarity in ambiguity, orchestrate cross‑functional execution, and own outcomes end‑to‑end. This role is perfect for a technical program/people leader who can go deep on the work while driving scale—a driver, not a passenger—and who thrives on aligning fast and executing faster.
Key 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.
Cross‑Functional Execution
- Align Product, Engineering, Clinical, and Customer teams around priorities; drive decisions and unblock fast.
- Translate ambiguous problem statements into clear problem definitions, milestones, and acceptance criteria.
- Coordinate data pipelines, annotations, experimentation, and evaluation—shipping production‑ready ML with reliability.
Technical Depth & MLOps
- 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).
People & Scale
- Mentor ML engineers/data scientists; set clear expectations, feedback loops, and growth paths.
- Improve the system—templates, playbooks, runbooks, postmortems—to compound team impact as we scale.
Must-Have Qualifications
- 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.
- Working knowledge of modern ML/LLM tooling (Python, PyTorch/TensorFlow, experiment tracking, data/feature stores, eval frameworks, model observability).
- 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.
Bonus
- 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.
- Experience mentoring/hiring ML talent and leading vendors/partners.
What we offer
- 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
How to Apply
Please submit your resume and a brief cover letter to careers@autonomize.ai explaining why you are the ideal candidate for this role. We are excited to meet someone who is eager to bring their skills, enthusiasm, and creativity to our team!