Manager, Applied AI, Advanced Informatics

Manager, Applied AI

At Regeneron, we use science and innovation to develop life-changing medicines for people with serious diseases. We are seeking a Manager, Applied AI to join our Advanced Informatics team, supporting health data systems and analytical pipelines across the organization. In this role, you will design and validate applied AI/ML solutions against complex health data and clinical ground truth, while collaborating with senior applied AI leaders, clinical informaticists, data engineers, and production ML engineers to build reusable analytical capabilities the broader informatics team depends on.

This position offers the opportunity to contribute to a fast-growing, science-driven organization making a meaningful difference to patients worldwide.

When & where:

Location:

Tarrytown, NY, Armonk, NY, or Warren, NJ

Discover your role:

Frame clinical and business informatics challenges into well-scoped AI/ML problem statements with clear success criteria

Design and build ML pipelines — data ingestion, feature engineering, training, and evaluation — alongside production engineering

Run experiments, benchmarks, and ablation studies to validate model performance and guide modeling decisions

Partner across clinical informatics, data engineering, and ML engineering to bring models into real informatics workflows

Track advances in foundation models, LLMs, and retrieval-augmented generation, and apply them to biomedical and health data

Document research findings and contribute to internal reports, publications, or conference presentations

Explain model behavior, limitations, and performance in terms both technical and non-technical team members can act on

This role requires:

Bachelor's degree in Computer Science, Machine Learning, Data Science, Biomedical Informatics, Statistics, or related field;
Master's or Ph.D. strongly preferred with 4–6 years + of progressive experience in applied AI/ML, with demonstrated ability to independently develop and evaluate models (Ph.D. graduates with relevant research experience may be considered)

Solid grounding in supervised, unsupervised, and self-supervised learning, deep neural networks, and modern ML frameworks (PyTorch, Tensor Flow, or equivalent)

Strong Python skills across the scientific ML stack (scikit-learn, Hugging Face Transformers, pandas, Num Py)

Experience designing and evaluating NLP or multimodal models, including LLM fine-tuning or prompt engineering

Comfort with experiment tracking, model versioning, and reproducible research practices (MLflow, W&B, DVC, or similar)

Familiarity with cloud-based ML infrastructure (AWS Sage Maker, GCP Vertex AI, Azure ML, or equivalent)

Experience with health or life sciences data — EHR/EMR, claims, clinical notes, genomic, or imaging data

Familiarity with medical terminologies and ontologies (SNOMED CT, ICD-10/11, LOINC, RxNorm, OMOP CDM)

Published work or open-source contributions in applied ML, NLP, or computational biomedicine

Experience with MLOps, CI/CD for ML, or model observability in production

Familiarity with federated learning, privacy-preserving ML, or regulated-environment data use agreements

Does this sound like you? Apply now to take your first step towards living the Regeneron Way! We are committed to building a workplace with an inclusive culture. 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.

Where necessary, we disclose salary ranges for roles in all countries in which we operate. The…