ML Engineer; R37

Position: ML Engineer (R37)
Remote, USA

Full time

R

At R1, we're transforming how healthcare works by combining nearly two decades of revenue cycle expertise with advanced technology, including analytics, AI, intelligent automation and workflow orchestration. We pair that technology with the irreplaceable expertise of our people to help hospitals, health systems and medical groups improve financial performance, simplify administrative complexity and create better experiences for patients and providers.

All Together Better defines our culture and the way we work. We're a diverse, global team united by a shared mission to make healthcare work better for all. Across technology, operations and support functions, our people bring deep expertise, empathy and ingenuity to the work we do. Here, collaboration fuels progress, adaptability sparks innovation and every voice can help shape what's next for R1 and the future of healthcare.

** About R37*
* R37 is R1's AI innovation lab, building technology to transform healthcare.

Our flagship platform, Phare OS, uses AI and automation to improve critical pre-bill workflows, including authorization, utilization management, documentation and coding. By identifying and resolving issues before claims are submitted, Phare OS helps prevent denials, improve reimbursement and move revenue cycle work upstream.

What makes R37 different is the opportunity to build advanced AI at real-world scale. R1 works across 95 of the top 100 U.S. health systems, giving R37 access to the data, workflows and reach needed to make an immediate impact:

+ 180M+ claims

+ 550M+ patient encounters

+ 1.2B+ workflow actions and outcomes annually

This is startup-level ownership with enterprise-level impact. You'll build technology that moves from idea to real healthcare environments, solving complex problems at scale and changing how healthcare works.

As our Machine Learning Engineer, you will help accelerate the development and deployment of AI-powered solutions by bridging the gap between research and production. Every day you will build and optimize machine learning infrastructure, develop scalable AI systems that solve complex business problems, and collaborate with researchers, engineers, and domain experts to bring innovative models into production. To thrive in this role, you must be passionate about applied AI, experienced in building and deploying machine learning systems at scale, and comfortable transforming ambiguous challenges into measurable business outcomes.

Here's what you will experience working as a Machine Learning Engineer:

+ Design and develop scalable AI systems for retrieval, ranking, categorization, and generative AI over large-scale unstructured healthcare data

+ Design, build, and operate AI/ML Systems end-to-end: from problem framing and model selection to production build and deployment, to ongoing improvement.

+ Work backwards from complex business problems to define AI abstractions and system architectures that are scalable, explainable, and maintainable

+ Design ranking and triage models that determine how work is routed between AI agents and human operators

+ Partner closely with software engineers, product managers, clinicians, and operators to ensure AI/ML systems deliver measurable business value

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* Required Skills:

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* + Strong experience designing, building, and deploying production AI/ML systems and services.

+ Experience building and scaling 0→1 AI products from prototype to production.

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Experience with model evaluation, benchmarking, experiment tracking, validation methodologies, and ML lifecycle management.

+ Experience developing large-scale AI applications involving retrieval systems, ranking models, generative AI, or other advanced machine learning technologies.

+ Proven ability to…