Senior Applied AI Engineer

Role overview Build and deploy applied AI systems that support clinical and revenue-cycle work in healthcare. The role covers the full path from exploring a solution to operating it in production, with work spanning models, integrations, and scalable inference systems.

Responsibilities - Design and deploy AI features for clinical and revenue-cycle workflows. - Develop and improve machine-learning models for healthcare-specific applications. - Build scalable model-serving and inference pipelines. - Own AI features through research, implementation, and production deployment. - Partner with product, engineering, customer teams, and clinical experts to deliver solutions and validate outputs. - Contribute to systems for clinical documentation, coding, denials management, and operator or clinician copilots.

Requirements - At least five years of experience building and deploying machine-learning systems in production. - Strong foundations in machine learning and software engineering. - Experience with Python and PyTorch or TensorFlow. - Experience with cloud infrastructure. - Ability to work through ambiguous, real-world problems with ownership and execution focus. - Clear communication and high standards for delivered work.

Nice to have - Familiarity with healthcare workflows, clinical systems, or revenue-cycle operations. - Experience integrating with electronic health record or revenue-cycle platforms.

Benefits and work setup - Full-time role based in New Jersey or remote.