Remote job
Sr AI/ML Engineer, Data Product & AI
Job details
About this role
Role overview
Own the lifecycle of production AI/ML capabilities for health-focused products, from framing a problem and designing models through evaluation, deployment, monitoring, and ongoing improvement. The role bridges applied research and production engineering, with work spanning predictive systems and generative AI. Close partnership with product, engineering, and clinical and regulatory stakeholders supports reliable, safe deployment at scale.
Responsibilities - Architect AI/ML capabilities from concept and experimentation through training, evaluation, and production release. - Build and improve predictive or generative features using methods such as model selection, prompting, retrieval, feature engineering, fine-tuning, or retraining. - Define evaluation measures, benchmarks, and monitoring; identify system risks and drive mitigations and responsible AI practices. - Guide technical decisions that balance model quality, latency, cost, safety, and regulatory requirements. - Work with engineers and architects to deploy and scale systems, and improve training, serving, and CI/CD pipelines. - Coordinate with research, commercial, product, legal, and regulatory partners; explain technical methods and results to varied audiences.
Requirements - A technical bachelor’s degree with typically 5–8 years of related experience, a master’s with 2–5 years, or a PhD with 0–2 years. - Strong computer science fundamentals and hands-on Python experience with modern AI/ML libraries and frameworks. - Experience taking AI/ML systems into production and operating them reliably, including evaluation, deployment, monitoring, and MLOps. - Experience building cloud-based AI/ML solutions and working with large datasets in distributed environments. - Familiarity with modern software engineering and testing practices.
Benefits and work setup
The role is home-office based and does not require living near an assigned office. Hybrid work may be available for people within typical commuting distance of a site; a flexible work option is also mentioned.