If you want a real AI engineering role (not just “build a model, toss it over the wall”), this one is about shipping AI features into production, measuring performance, and tying the work to business outcomes in healthcare revenue cycle operations.
About R1
R1 is a healthcare revenue management leader using analytics, automation, AI, and workflow orchestration to improve patient experience and hospital financial performance. Their R37 group operates like a startup inside the company, focused on AI-first revenue cycle modernization at enterprise scale.
Schedule
- Full-time, Remote (USA)
- Interview note: in-person interview at a talent hub (SF, NY, Austin, or Chicago). Travel provided if you’re outside those areas.
- Compensation: $140,000–$200,000/year (location, skills, experience dependent)
- Bonus eligible (annual bonus plan)
What You’ll Do
- Build AI features for unstructured healthcare data (retrieval, ranking, categorization, and generative AI)
- Support AI projects end-to-end, from requirements to deployment, with guidance from senior engineers
- Help implement production-ready AI systems, including monitoring and operational practices
- Use evaluation datasets and metrics to measure model quality and connect results to business impact
- Collaborate with product managers and senior engineers, and contribute to team knowledge sharing
What You Need
- Experience working with AI/ML systems in production (especially search, ranking, or generative AI)
- Some experience prototyping and helping move AI work from concept to implementation
- Understanding of the AI development lifecycle (model selection through basic productionization)
- Ability to connect modeling work to business value through stakeholder collaboration
- Hands-on with PyTorch or TensorFlow and pre-trained models (Hugging Face)
- Exposure to deployment tooling like Databricks, AWS Bedrock, or Azure ML
Benefits
- Competitive benefits package (details vary by plan, but includes standard healthcare/coverage options)
- Bonus plan eligibility
- Work with a high-impact team building AI that’s meant to run in the real world, not just demos
Real talk: this salary band suggests they’re not looking for “I took an ML course” energy. They want someone who’s at least been around production AI and knows the pain of evaluation, monitoring, and weird edge cases. If that’s not you yet, you’re better off targeting their Data Ops / Analytics roles first and building the AI muscle from there.
Happy Hunting,
~Two Chicks…