
Job Overview
Location
New York, New York, United States
Job Type
Full-time
Category
Machine Learning Engineer
Date Posted
April 21, 2026
Full Job Description
đź“‹ Description
- • Join Capital Rx, Inc. as a Machine Learning Engineer to infuse cutting-edge AI/ML/GenAI into pharmacy benefits, enabling increased productivity and magical experiences in products and services while contributing to a mission-driven effort to rebuild trust in healthcare.
- • Day to day, you will develop and productionize ML solutions for document understanding, search, QnA, GenAI, and virtual agents; build backend services in Python; design APIs for AI model integration; create tools for large-scale data processing and ETL; participate in code reviews and testing; troubleshoot AI model and deployment issues; develop validation processes for ML integrity; document development workflows; and ensure HIPAA-compliant handling of healthcare data.
- • You will be part of Judi Health, an enterprise health technology company comprising Capital Rx (a public benefit corporation PBM), Judi Health™ (health benefit management), and Judi® (the Enterprise Health Platform), working collaboratively in a high-growth startup environment focused on transforming healthcare through technology.
- • In this role, you will deepen your expertise in LLMs, multimodal models, RAG, and MLOps; gain end-to-end experience in deploying AI systems in regulated healthcare settings; strengthen your software engineering practices; and contribute to impactful innovations that improve care delivery for employers, health plans, and patients.
Skills & Technologies
About Capital Rx, Inc.
Capital Rx is a full-service pharmacy benefit manager and healthcare technology company that modernizes drug pricing and claims processing. Its cloud-based platform, JUDI, connects every aspect of the pharmacy ecosystem, enabling transparent, pass-through pricing and real-time analytics. The company administers formularies, rebates, and networks for employers, health plans, and government entities, aiming to lower prescription costs and improve patient outcomes.
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