Senior Applied AI Engineer

About the Role

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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 a Senior Applied 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

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• 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 capabilit...