Machine Learning Infrastructure Engineer

San Francisco

Ambience

Reduce clinician burnout, improve system efficiency, and enable high quality care.

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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:

We’re looking for a Machine Learning Infrastructure Engineer to join our AI Platform team. This is a high-leverage role focused on building and scaling the core infrastructure that powers every AI system at Ambience. You’ll work closely with our ML, data, and product teams to develop the foundational tools, systems, and workflows that support rapid iteration, robust evaluation, and production reliability for our LLM-based products.

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

What You’ll Do:

  • You have 5+ years of experience as a software engineer, infrastructure engineer, or ML platform engineer

  • You’ve worked directly on systems that support ML research or production workloads – whether training pipelines, evaluation systems, or deployment frameworks

  • You write high-quality code (we primarily use Python) and have strong engineering and systems design instincts

  • You’re excited to work closely with ML researchers and product engineers to unblock them with better infrastructure

  • You’re pragmatic and care deeply about making tools that are reliable, scalable, and easy to use

  • You thrive in fast-paced, collaborative environments and are eager to take ownership of ambiguous problems

Who You Are:

  • Design, build, and maintain the infrastructure powering ML model training, batch inference, and evaluation workflows

  • Improve internal tools and developer experience for ML experimentation and observability

  • Partner with ML engineers to optimize model deployment and monitoring across clinical workloads

  • Define standards for model versioning, performance tracking, and rollout processes

  • Collaborate across the engineering team to build reusable abstractions that accelerate AI product development

  • Drive performance, cost efficiency, and reliability improvements across our AI infrastructure stack


Pay Transparency

We offer a base compensation range of approximately $200,000-300,000 per year, with the addition of significant 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. If your expectations fall outside of this range, we still encourage you to apply—our approach to compensation considers a range of factors to ensure alignment with each candidate's unique needs and preferences.

Being at Ambience: 

  • An opportunity to work with cutting edge AI technology, on a product that dramatically improves the quality of life for healthcare providers and the quality of care they can provide to their patients

  • Dedicated budget for personal development, including access to world class mentors, advisors, and an in-house executive coach

  • Work alongside a world-class, diverse team that is deeply mission aligned

  • Ownership over your success and the ability to significantly impact the growth of our company

  • Competitive salary and equity compensation with benefits including health, dental, and vision coverage, quarterly retreats, unlimited PTO, and a 401(k) plan

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Tags: Engineering LLMs Machine Learning ML infrastructure Model deployment Model training OpenAI Pipelines Python Research

Perks/benefits: Career development Competitive pay Equity / stock options Health care Startup environment Team events Unlimited paid time off

Region: North America
Country: United States

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