ML Engineer, Frontier AI

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 innovative technology helps healthcare providers focus on delivering exceptional care by eliminating administrative burdens that divert their attention from patients and impactful work. Ambience delivers real-time, coding-aware documentation and clinical workflow support across ambulatory, emergency, and inpatient settings at some of the top health systems in North America.
Our dedicated teams operate with relentless ownership, striving to develop the best solutions for our health system partners. We value candor, positivity, and deep thought—expecting excellence from each other because we understand the significance of the problems we are solving. Recognized for our impactful work, Ambience was ranked #1 for Improving the Clinician Experience in the KLAS Research Emerging Solutions Top 20 Report, featured by Fast Company as one of the Next Big Things in Tech, named among the best AI companies in healthcare by Inc., and selected as a LinkedIn Top Startup in 2024 and 2025. Supported by prominent investors like Oak HC/FT, Andreessen Horowitz (a16z), OpenAI Startup Fund, and Kleiner Perkins, we are just getting started on our mission to revolutionize healthcare through AI innovation.
About The Role
As a Staff Machine Learning Engineer on the Frontier AI team at Ambience, you will be at the forefront of tackling the most challenging model quality problems across our clinical AI products. Your work will encompass foundational coding models, adaptive scribing, voice agents, long-context chart understanding, and clinical reasoning. This role is highly impactful, requiring you to define research directions, design learning loops, and drive comprehensive model quality improvements that yield long-term benefits.
Our products operate in real-world healthcare environments with unique constraints such as proprietary ontologies, complex EHR data, high compliance standards, and clinician workflows where both latency and accuracy are critical. You will bring your research instincts and engineering discipline to push the boundaries of what is possible in clinical AI, ensuring our models perform reliably and efficiently under these demanding conditions.
This hybrid engineering position involves working onsite at our San Francisco office three days a week, fostering collaboration and innovation within our team. Your contributions will directly influence the development of advanced AI solutions that improve patient outcomes and streamline healthcare workflows.
Qualifications

• 5+ years of experience in ML engineering or applied research, with a proven track record of deploying model improvements in production environments.
• Deep expertise in reinforcement learning and deep learning, developed through industry or research experience.
• Strong publication record at top-tier venues such as NeurIPS, ICML, ICLR, ACL, EMNLP (a plus).
• Proficiency in Python and experience with deep learning frameworks, preferably PyTorch.
• Experience with preference learning, reinforcement learning with human feedback (RLHF), retrieval-augmented generation, or multi-label classification.
• Ability to translate research insights into scalable, production-ready systems.
• End-to-end ownership of model quality improvements, from failure analysis to deployment and measurement.
• Experience operating at the research-to-production frontier, especially on complex, high-stakes problems.
• Strong communication skills and the ability to influence technical decisions across teams.
• Passion for healthcare or mission-driven industries and a desire to make a meaningful impact.

Responsibilities

• Lead foundational model research by identifying failure modes, hypothesizing solutions, and making architecture decisions on complex clinical AI problems.
• Design and implement learning loops that leverage real-world signals—including clinician edits, coder corrections, and audit outcomes—to continuously improve model performance.
• Enhance the quality of Chart Chat by improving grounding, retrieval mechanisms, and reasoning capabilities to handle diverse clinical questions over longitudinal patient records.
• Optimize model latency, accuracy, and cost through techniques such as routing, distillation, speculative decoding, and quantization, ensuring safe and effective deployment.
• Contribute to the development of population-level clinical reasoning, enabling models to analyze and infer across large patient datasets.
• Stay current with research developments in reinforcement learning, deep learning, and clinical NLP, and lead experiments to keep Ambience at the forefront of clinical AI innovation.
• Collaborate with cross-functional teams to translate research insights into scalable production systems that meet healthcare compliance standards.

Benefits

• Comprehensive medical, dental, and vision coverage for employees and dependents.
• 401(k) plan with a company match of up to 3% of base salary.
• Remote-friendly culture with full equipment provisioning to support effective work from anywhere.
• Parental leave policies to support family needs.
• Annual company-wide off-sites, team retreats, and regular gatherings, with travel and accommodation covered.
• Flexible time off policy with no annual cap, alongside company holidays and a dedicated holiday shutdown period from December 24 to January 1.
• Supportive environment focused on professional growth, ownership, and impactful work in healthcare AI.

Equal Opportunity
Ambience Healthcare is an equal opportunity employer committed to fostering a diverse and inclusive workplace. We do not discriminate based on race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, veteran status, genetic information, or any other legally protected characteristic. We