Associate Software Developer Jobs in Stony Point, NY

Build our future together: At Regeneron, we use science and innovation to develop life‑changing medicines for people with serious diseases. We are seeking an Associate Manager, Production AI/ML Engineering to join our Advanced Informatics team.

Location: Tarrytown or Armonk, NY or Warren, NJ

In this role, you will architect and scale the computational ecosystem that powers our AI/ML applications—transforming population‑scale clinical and claims data into reliable, production‑grade model inference—while collaborating closely with Applied AI managers, clinical informaticists, and data governance partners.

• 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.

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Biomedical Informatics, or related field (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.

Salary Range (annually): $109,900.00 – $179,300.00 (based on country of employment, specific role level, and candidate skills and experience).

Benefits may include: annual bonuses or other incentive plans, equity awards, pension or retirement benefits, 401(k) company match, health and wellness programs, fitness centers, insurance benefits (medical, dental, vision, life and disability), paid time off, and family support benefits. Additional information will be provided during the recruitment process.

Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion or belief (or lack thereof), sex, sexual orientation, gender identity or expression, gender reassignment, marital or civil partnership status, civil status, pregnancy or parental status, age, disability, nationality, citizenship status, ethnic or national origin, membership of the Traveler community, familial status, genetic information, military or veteran status, or any other characteristic protected under applicable law. Where required, we will provide reasonable accommodation to applicants with known disabilities or chronic illnesses during the recruitment process, unless such accommodation would impose undue hardship.