Associate Manager, Production AI/ML Engineering, Advanced Informatics

Regeneron develops life-changing medicines for people with serious diseases and is seeking an Associate Manager, Production AI/ML Engineering to join its Advanced Informatics team. The role architects and scales AWS and Kubernetes infrastructure, production ML pipelines, APIs, MLOps systems, and model-serving capabilities using clinical and claims data while ensuring operational reliability, governance, and compliance.

Responsibilities:

• Architect and maintain a scalable AWS/Kubernetes ecosystem supporting model training, batch inference, and real-time serving
• Design and maintain production-grade ML pipelines over population-scale clinical and claims data, including ingestion, normalization, and transformation across controlled terminologies (SNOMED CT, ICD-10/11, LOINC, RxNorm, OMOP CDM)
• Develop RESTful APIs that reliably expose model inference to downstream teams and applications
• Operationalize models from the Applied AI team — owning deployment, versioning, rollback, and A/B testing
• Build MLOps infrastructure (CI/CD, feature stores, model registries) and champion engineering best practices
• Own monitoring, alerting, and incident response for production ML systems
• Partner with data governance and compliance to ensure pipelines and deployments adhere to data use agreements and de-identification standards
• Shape capacity planning and the long-term technical roadmap for the team's AI/ML platform

Requirements:

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Biomedical Informatics, or related (Master's preferred) with 7–9 years of progressive ML/platform/software engineering experience with an infrastructure focus
• Proven experience designing and operating ML infrastructure at enterprise scale on AWS (SageMaker, ECS, EC2, S3, Lambda, or equivalent)
• Strong Kubernetes expertise: cluster management, workload scheduling, autoscaling, and deploying containerized ML services in production
• Proficiency building and maintaining RESTful APIs; experience with API design, versioning, performance tuning, and integration with ML serving frameworks
• Hands-on experience with Postgres: schema design, query optimization, and integration into data and ML pipelines
• Expert-level Python and SQL; strong software engineering fundamentals including Git, modular design, testing, and CI/CD
• Proficiency with MLOps tooling: experiment tracking (MLflow, W&B), model registries, containerization (Docker), and pipeline orchestration (Airflow, Prefect, or similar)
• Informatics knowledge with health or life sciences data — EHR/EMR records, claims data, clinical notes, or administrative data is preferred