Senior AI Engineer

Posted 5 Days Ago
San Francisco, CA, USA
In-Office
200K-250K Hourly
Senior level
Artificial Intelligence • Healthtech • Information Technology • Software • Generative AI
The Role
Build and productionize LLM-based systems for home health: train and fine-tune open-source models, create eval and monitoring pipelines, design accuracy metrics and feedback loops, build scalable inference and agentic infrastructure, and prototype then harden reliable, cost-efficient AI systems used by clinicians.
Summary Generated by Built In
About the Role

Roger is an AI platform that frees home health clinicians from paperwork so they can focus on what matters: delivering life-changing care to our most vulnerable elderly patients in the comfort of their homes. Backed by leading healthcare investors like SignalFire, we've powered millions of visits, deployed to thousands of clinicians, and we're just getting started.

The administrative work behind home health is messy, unstructured, and high-stakes. From clinical documentation to the operational busywork that organizations serving these vulnerable populations face every day, turning dense, nuanced information into accurate records requires LLM systems that extract structure from unstructured data, validate their own outputs, learn from a vast and growing dataset, and continuously improve in accuracy.

We are now looking for an AI Engineer to build the intelligence layer at the core of Roger: training and fine-tuning models on our data, building the eval and monitoring infrastructure that keeps them accurate, and shipping LLM-powered workflows that clinicians rely on every day. There is a wide gap between a demo of an AI product and one that actually works for real clinicians caring for real patients, and we are hiring engineers who build on the right side of that gap.

What You'll Do
  • Train and fine-tune open source models, leveraging our vast proprietary dataset to push accuracy beyond what off-the-shelf models can do.

  • Build eval datasets and pipelines that let us measure model accuracy rigorously and improve it continuously.

  • Design how we measure accuracy in the first place: the metrics, harnesses, and feedback loops that turn real clinical outcomes into measurable model improvements.

  • Build scalable, cost-efficient inference infrastructure with great monitoring and observability.

  • Build better agentic infrastructure and partner on the interfaces that turn model capability into a great clinician experience.

  • Stay at the frontier: keep up with the latest research, frontier model capabilities, and open source frameworks, and bring the best of it into production.

  • Prototype quickly, then harden into scalable, secure, and reliable production systems.

You Might Be a Good Fit If You Have
  • 7+ years of professional software engineering experience, with meaningful depth in AI/ML.

  • Experience training, fine-tuning, or evaluating LLMs and open source models, with real opinions about what works and what does not.

  • Shipped real AI software to real users. You can describe something you built, what broke, and how you fixed it.

  • Strong instincts for evals, observability, and the feedback loops that turn user feedback into measurable improvement.

  • Experience building agentic systems: tool use, generator and critic loops, planners and executors, and orchestration where one agent's output drives another's work.

  • Comfort building infrastructure that is fast, reliable, and cost-efficient at scale.

  • Startup experience shipping real features in high-growth environments.

  • A product mindset, comfort across the stack, and the ability to operate in ambiguity without a clean spec.

  • High standards for reliability and accuracy when real clinicians and patients depend on your work.

Why Join Us?

🏥 Platinum health, dental, and vision insurance

🏖️ Flexible PTO

🤖 Be at the forefront of LLM innovation in healthcare

🚀 Founded by AI Researchers from Cornell and Amazon Alexa

👩‍⚕️ Make a tangible difference in the lives of clinicians and patients

🧠 Work on a mission that matters, backed by AI innovation and top-tier investors

 

Make a Real Difference: Hear from our Users

 

👨‍⚕️ “If I had to give Roger a rating out of 10, I’d give it an 11! You guys changed my life!!”

- G.M. from San Francisco, Registered Nurse

 

👩‍⚕️ “Roger AI saves me hours per day. I can easily focus on my patients now too.”

- J.L. from Tucson, Registered Nurse

 

👩‍⚕️ “Being a single mom is tough, but with Roger I can take the time to go to my daughter’s soccer game and also pursue further education.”

- T.M. from Dallas, Licensed Vocational Nurse

 

If you're interested in joining a fast-growing healthcare AI startup, we'd love to hear from you TODAY!
In person and remote opportunities available.

Skills Required

  • 7+ years of professional software engineering experience with meaningful depth in AI/ML.
  • Experience training, fine-tuning, or evaluating LLMs and open source models.
  • Shipped real AI software to real users and diagnosed/fixed production issues.
  • Strong instincts for evaluations, observability, and feedback loops linking user outcomes to model improvement.
  • Experience building agentic systems: tool use, generator/critic loops, planners, executors, and orchestration.
  • Experience building scalable, cost-efficient inference infrastructure with monitoring and observability.
  • Comfort prototyping quickly and hardening systems into secure, reliable production at scale.
  • Product mindset, full-stack comfort, and ability to operate in ambiguity without a clean spec.
  • Startup experience shipping features in high-growth environments.
  • High standards for reliability and accuracy when clinicians and patients depend on your work.
Am I A Good Fit?
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The Company
HQ: San Francisco, CA
12 Employees
Year Founded: 2023

What We Do

Roger is empowering the home health care industry with breakthrough generative AI technology to alleviate organizations from staffing shortages. Roger Docs allows home health clinicians to complete OASIS and routine documentation in minutes instead of hours. Roger is fully implemented at agencies serving tens of thousands of patients each day.

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