
Ambience Healthcare’s AI technology for scribing, coding, and patient summaries has been deployed at health systems such as Cleveland Clinic, UCSF, St. Luke’s Health System, John Muir Health, and…

Ambience Healthcare’s AI technology for scribing, coding, and patient summaries has been deployed at health systems such as Cleveland Clinic, UCSF, St. Luke’s Health System, John Muir Health, and…
Location: San Francisco
Founded: 2020
Product: Ambient AI platform for clinical documentation, coding, CDI, and workflow automation
EHR integrations: Epic, Cerner (Oracle), athenahealth
Notable customers: Cleveland Clinic, UCSF, St. Luke's Health System, John Muir Health, Memorial Hermann
Total disclosed funding (evidence): Approximately $100M after Feb 2024 Series B
Clinical documentation burden, coding accuracy, CDI, and clinical workflow inefficiencies in healthcare systems.
2020
Hospitals and Health Care
70,000,000
Round reported to bring total disclosed funding to about $100M
“Backed by institutional investors including Oak HC/FT, Andreessen Horowitz (a16z), Kleiner Perkins, OpenAI Startup Fund, and Optum Ventures”
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About Us Here at Ambience, we never set out to be just another scribe. We’re building the AI intelligence platform that restores humanity to healthcare and drives meaningful ROI for health systems across the country.
Our technology helps providers focus on delivering great care by removing the administrative burden that pulls them away from patients and away from their most impactful work. Ambience delivers real-time coding-aware documentation and clinical workflow support across ambulatory, emergency and inpatient settings at the top health systems in North America.
Our teams operate relentlessly with extreme ownership to build the best solutions for our health system partners. We value candor, positivity and deep thought — and we expect a lot from each other because we know the problems we’re solving truly matter.
Ambience was ranked #1 for Improving the Clinician Experience in the KLAS Research Emerging Solutions Top 20 Report, recognized by Fast Company as one of the Next Big Things in Tech, named one of the best AI companies in healthcare by Inc., and selected as a LinkedIn Top Startup in 2024 and 2025. We’re backed by Oak HC/FT, Andreessen Horowitz (a16z), OpenAI Startup Fund, and Kleiner Perkins — and we’re just getting started. The Role 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.
What You’ll Own
Who You Are
Compensation We offer a base compensation range of approximately $250,000-350,000 per year, exclusive of equity. This intentionally broad range provides flexibility for candidates to tailor their cash and equity mix based on individual preferences. Our compensation philosophy prioritizes meaningful equity grants, enabling team members to share directly in the impact they help create.
Are you outside of the range? We encourage you to still apply: we take an individualized approach to ensure that compensation accounts for all of the life factors that matter for each candidate.
Life at Ambience Working at Ambience means opting into a high-ownership, high-trust environment built for people who want to grow fast, operate decisively and focus on work that matters. This could be the right place for you if you want to
To help you do your best work, we pair these expectations with benefits intentionally designed to help you feel supported and safe at Ambience and beyond. Some of our key benefits include
Ambience Healthcare is an equal opportunity employer and is committed to building a diverse and inclusive workplace. We do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, genetic information, or any other legally protected status. We encourage applicants from all backgrounds to apply.
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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.
Publications at top-tier venues (NeurIPS, ICML, ICLR, ACL, EMNLP, etc.) are a strong plus.
Research to Production
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).
End-to-End Ownership
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.
Mission-Aligned
Passion for healthcare or other high-stakes, mission-driven industries.
Thrives in a fast-paced environment; takes extreme ownership of deliverables.
Nice-to-haves
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.