Staff ML Engineer, Frontier AI
About The Position
As a Staff ML Engineer on the Frontier AI team at Ambience, you'll own the hardest model quality problems across our clinical AI products — foundational coding models, adaptive scribing, voice agents, long-context chart understanding, and clinical reasoning. This isn't a platform or infrastructure role. You'll set research direction, design learning loops, and drive end-to-end model quality improvements that compound over time. Ambience ships advanced clinical AI in real-world healthcare settings. The models that power our products operate under constraints you won't find in typical ML roles — proprietary ontologies, messy EHR data, high compliance stakes, and clinician workflows where latency and accuracy both matter. You'll bring deep research instincts and engineering discipline to push the frontier on all of it. Our engineering roles are hybrid - working onsite at our San Francisco office three days per week.
Requirements
- Deep RL and Deep Learning Expertise
- 5+ years of ML engineering or applied research experience, with a strong track record of shipping model improvements in production.
- Deep expertise in reinforcement learning and deep learning, developed in industry or a research setting.
- Comfortable spanning research and engineering — architecture decisions, training runs, fine-tuning pipelines, and production deployment.
- Experience with preference learning, RLHF, retrieval-augmented generation, or multi-label classification.
- Strong Python fundamentals and experience with deep learning frameworks (PyTorch preferred).
- Can point to model quality improvements driven end to end: from identifying a failure mode to shipping and measuring a fix.
- Has operated at the frontier of a hard problem, not just applied standard techniques.
- Staff-level scope — has owned research directions and influenced technical decisions across teams.
- Passion for healthcare or other high-stakes, mission-driven industries.
- Thrives in a fast-paced environment; takes extreme ownership of deliverables.
Nice To Haves
- Publications at top-tier venues (NeurIPS, ICML, ICLR, ACL, EMNLP, etc.) are a strong plus.
- Experience with clinical data: EHR systems, FHIR, medical coding ontologies, or clinical NLP.
- Prior work in healthcare AI or other regulated, high-stakes domains.
- Open-source contributions to ML libraries, benchmarks, or evaluation frameworks.
Responsibilities
- Own foundational model research. Identify failure modes, form hypotheses, and drive architecture decisions on hard clinical AI problems — medical coding, adaptive scribing, chart understanding, and more.
- Build compounding learning loops. Design systems that turn real-world signals — clinician edits, coder corrections, audit outcomes — into fast, safe model improvements.
- Improve Chart Chat quality. Drive better grounding, smarter retrieval, and reasoning that holds up under the real diversity of clinical questions over complex longitudinal patient records.
- Push latency, accuracy, and cost simultaneously. Apply the right optimization levers — capability routing, distillation, speculative decoding, quantization — and know when each is safe.
- Contribute to population-level clinical reasoning. Help build toward a layer of clinical intelligence that reasons not just over individual patients, but across patient populations at scale.
- Stay at the cutting edge. Distill insights from recent research — particularly in RL, deep learning, and clinical NLP — and drive experiments that keep Ambience at the frontier of clinical AI.
Benefits
- Comprehensive medical, dental, and vision coverage for you and your dependents
- 401(k) with a company match of up to 3% of base salary
- A remote-friendly culture (with a San Francisco HQ) and full equipment provisioning to ensure you can work effectively from wherever you’re based.
- Parental leave to support your family needs
- Annual company-wide off-sites, team off-sites and regular team lunches and all-hands gatherings, with travel, lodging and meals covered
- Flexible time off with no annual cap, company-wide holidays and an annual holiday shutdown from December 24–January 1 designed to support real rest and long-term sustainability.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
