Staff AI Engineer (Clinical LLMs & Speech)

About Us:

Ambience is developing the most capable AI systems for healthcare and medicine. As healthcare costs soar to 17.3% of US GDP and a projected shortage of 100,000 physicians within the next decade, the need for AI is critical. Our frontline healthcare workers are overwhelmed, with only 27% of the average clinician's day spent on direct patient care.

Our vision is to advance healthcare by empowering clinicians with safe, intelligent AI agents that improve quality, reduce costs, and enhance both patient and provider experiences.

Headquartered in San Francisco, we have secured $100M in funding from top investors, including Kleiner Perkins, OpenAI Startup Fund, Andreessen Horowitz, Optum Ventures, Human Capital, and Martin Ventures. We collaborate with leading AI experts such as Jeff Dean, Richard Socher, Pieter Abbeel, and AIX Ventures.

Join us in the endeavor of accelerating the path to safe & useful clinical super intelligence by becoming part of our community of problem solvers, technologists, clinicians, and innovators.

The Role:

As a Staff Machine Learning Engineer at Ambience, you will help guide the technical direction of our AI team, identifying the most impactful opportunities to build, refine, and deploy machine learning systems that enhance clinical outcomes. This role is both strategic and hands-on, requiring close collaboration with clinicians, product managers, and fellow engineers to turn cutting-edge research into production-grade solutions.

Our engineering roles are hybrid — working onsite at our San Francisco office three days per week.

What You’ll Do:

• Define and Drive the AI Roadmap: Co-develop a 12‑month technical plan balancing quick product wins with longer‑term research bets, and lead execution on near-term priorities.

• Build Trustworthy Evaluation Systems: Launch an automated evaluation pipeline tying offline metrics (precision, recall, latency) to live clinician feedback, surfacing quality trends in a single dashboard

• Deliver Measurable Quality Gains: Prototype and A/B-test model improvements that significantly reduce top user-reported error classes across multiple clinical applications.

• Level‑up our data engine: Design an active-learning loop that flags challenging clinical examples for re-labeling, reducing review time while improving downstream model performance.

• Stay at the cutting edge: Distill insights from recent research—particularly in LLMs, NLP, and speech recognition—and drive experiments that keep Ambience at the forefront of clinical AI.

Who You Are:

• Expert in ML and NLP Fundamentals

  • 7+ years in a production ML or research engineering role

  • Deep expertise with modern neural networks (e.g., transformers) and advanced evaluation techniques.

  • Strong fluency with recent AI literature and ability to translate research into practical applications.

• Production-Grade Software Engineer

  • Proficient in Python and deep learning frameworks (PyTorch preferred).

  • Comfortable with modern MLOps, CI/CD workflows for ML, and containerized deployments.

• Data-Centric AI Developer

  • Skilled at building and maintaining large, high-quality datasets.

  • Experienced in leveraging user feedback and active learning to improve model and data pipelines.

• Effective Interdisciplinary Collaborator

  • Able to work alongside clinicians, product managers, and fellow engineers

  • Strong communicator who can simplify complex ML concepts for diverse audiences

• Mission-Aligned

  • Passion for healthcare or other mission-driven industries (e.g., education, climate tech)

  • Thrives in a fast-paced, early-stage environment; takes extreme ownership of deliverables

• Nice-to-haves

  • Experience as an interviewer or hiring manager for ML roles.

  • Prior work in healthcare, clinical AI, or other regulated, high-stakes industries.

  • Open-source contributions to ML libraries, evaluation suites, or benchmarking tools.

Compensation

$250,000 - $350,000, with the addition of significant equity.

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.

Being at Ambience: 

• An