Manager, Applied AI, Advanced Informatics

Posted Yesterday
Be an Early Applicant
3 Locations
In-Office
151K-246K Annually
Senior level
Biotech • Pharmaceutical
The Role
Design and develop applied AI/ML solutions for health informatics: frame ML problems, build and evaluate models and pipelines, run experiments and ablations, collaborate with clinical informaticists and engineers to integrate models, document research, and communicate results to technical and non-technical stakeholders.
Summary Generated by Built In

Build a future together

The Manager, Applied AI is a research-facing technical role within the Advanced Informatics team responsible for designing and developing applied AI solutions across health data systems and analytical pipelines. This role works closely with senior applied AI leaders to formulate ML problems against complex health data, validate methods against clinical ground truth, and build reusable analytical capabilities that the broader informatics team depends on.

The ideal candidate brings solid grounding in AI/ML theory, hands-on experience applying it to real-world data problems, and is excited to deepen their expertise at the intersection of machine learning and health informatics.

When & where:
This can be a remote position in the US or on-site position at our Tarrytown, NY, Armonk, NY or Warren, NJ offices. 

Discover your role:

  • Design and develop applied AI/ML solutions for health informatics use cases, from problem framing and data exploration through model development and evaluation.
  • Translate business and clinical informatics challenges into well-scoped AI/ML problem statements with clear success criteria.
  • Build and maintain ML pipelines including data ingestion, feature engineering, model training, and evaluation, in close collaboration with production engineering.
  • Conduct experiments, benchmarking, and ablation studies to validate model performance and inform modeling decisions.
  • Partner with clinical informaticists, data engineers, and production AI/ML engineers to integrate models into informatics workflows.
  • Stay current with advances in foundation models, LLMs, retrieval-augmented generation, and their application to biomedical and health data domains.
  • Contribute to research documentation, internal technical reports, and where appropriate, external publications or conference presentations.
  • Communicate model behavior, limitations, and performance clearly to both technical and non-technical stakeholders.

This role requires:

Bachelor's degree (BS) in Computer Science, Machine Learning, Data Science, Biomedical Informatics, Statistics, or a closely related field required. Ph.D. or Master's degree strongly preferred given the research-facing nature of this role.

Minimum Years of Experience: 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 at the lower end of this range.

Knowledge, Skills & Abilities (Required):

  • Solid understanding of supervised, unsupervised, and self-supervised learning; deep neural networks; and modern ML frameworks (PyTorch, TensorFlow, or equivalent).
  • Strong command of Python and the scientific ML stack (scikit-learn, HuggingFace Transformers, pandas, NumPy, etc.)
  • Experience designing and evaluating NLP or multimodal models, including fine-tuning or prompt engineering with large language models.
  • Proficiency with experiment tracking, model versioning, and reproducible research practices (MLflow, W&B, DVC, or similar).
  • Familiarity with cloud-based ML infrastructure (AWS SageMaker, GCP Vertex AI, Azure ML, or equivalent).
  • Ability to drive technical work independently and communicate findings clearly across teams.

Knowledge, Skills & Abilities (Preferred):

  • Experience with health or life sciences data — EHR/EMR records, claims data, clinical notes, genomic data, or imaging.
  • Informatics domain knowledge (strong plus): familiarity with medical terminologies and ontologies (SNOMED CT, ICD-10/11, LOINC, RxNorm, OMOP CDM) and machinable health data standards.
  • Published work or open-source contributions in applied ML, NLP, or computational biomedicine.
  • Experience with MLOps pipelines, CI/CD for ML, and model observability in production environments.
  • Familiarity with federated learning, privacy-preserving ML, or working with data use agreements in regulated environments.

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 final offer will be determined within the relevant range based on the country of employment, specific role level, and your skills and experience. In some countries, collective bargaining agreements (CBAs) may apply and influence certain elements of pay or benefits.  Regeneron offers a competitive and comprehensive total rewards package which may include, depending on country and role: annual bonuses or other incentive plans, equity awards, pension or retirement benefits, 401(k) company match, health and wellness programs, fitness centers, insurance benefits (e.g. medical, dental, vision, life and disability), paid time off, and family support benefits. For additional information about Regeneron benefits in the U.S., please visit https://careers.regeneron.com/en/working-at-regeneron/total-rewards/. For other locations, additional information will be provided during the recruitment process.  If you have any questions, please speak with your recruiter. 


Please be advised that at Regeneron, we believe we do our best work when we are together. For that reason, many roles are required to be performed on‑site. Please speak with your recruiter and hiring manager for more information about on‑site expectations for your role and location.


As part of the recruitment process, certain background checks may be conducted in accordance with the laws of the country where the position is based. The purpose of such checks is to verify certain information prior to the commencement of employment such as identity, right to work and educational qualifications.


For jobs in Canada: this posting is for an existing position.


Salary Range (annually)

$150,500.00 - $245,500.00

Skills Required

  • Bachelor's degree in Computer Science, Machine Learning, Data Science, Biomedical Informatics, Statistics, or related field
  • Master's degree or Ph.D. (strongly preferred for research-facing role)
  • 4-6 years of progressive experience in applied AI/ML (Ph.D. candidates may be considered)
  • Solid understanding of supervised, unsupervised, and self-supervised learning and deep neural networks
  • Experience with modern ML frameworks (PyTorch, TensorFlow, or equivalent)
  • Strong command of Python and scientific ML stack (scikit-learn, HuggingFace Transformers, pandas, NumPy)
  • Experience designing and evaluating NLP or multimodal models, including fine-tuning or prompt engineering with LLMs
  • Proficiency with experiment tracking, model versioning, and reproducible research practices (MLflow, W&B, DVC, or similar)
  • Familiarity with cloud-based ML infrastructure (AWS SageMaker, GCP Vertex AI, Azure ML, or equivalent)
  • Ability to drive technical work independently and communicate findings across teams
  • Experience with health or life sciences data (EHR/EMR, claims, clinical notes, genomics, imaging)
  • Informatics domain knowledge and familiarity with medical terminologies/ontologies (SNOMED CT, ICD-10/11, LOINC, RxNorm, OMOP CDM)
  • Published research or open-source contributions in applied ML, NLP, or computational biomedicine
  • Experience with MLOps pipelines, CI/CD for ML, and model observability in production
  • Familiarity with federated learning, privacy-preserving ML, or regulated data use agreements

Regeneron Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Regeneron and has not been reviewed or approved by Regeneron.

  • Healthcare Strength Medical, dental, and vision coverage is positioned as comprehensive, with Regeneron prescription drugs covered at 100% for those enrolled in the medical plan. Mental health support is also emphasized through EAP access and tools like Talkspace and the Journey app.
  • Equity Value & Accessibility Stock grants are described as available to all employees, strengthening the overall total-rewards package beyond base pay. Long-term incentives and stock-related rewards are repeatedly framed as meaningful components of compensation.
  • Parental & Family Support Paid parental leave is paired with fertility/adoption assistance and childcare-related support such as discounts and nanny services. Additional family-oriented resources extend to elder care, pet care, and education support like college coaching and tutoring.

Regeneron Insights

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The Company
HQ: Tarrytown, NY
15,000 Employees
Year Founded: 1988

What We Do

At Regeneron we believe that when the right idea finds the right team, powerful change is possible. As we work across our expanding global network to invent, develop and commercialize life-transforming medicines for people with serious diseases, we’re establishing new ways to think about science, manufacturing and commercialization. And new ways to think about health. Connect with us so we can learn more about you, and you can learn more about our biopharmaceutical medicines. And join us, as we build a future we believe in. Please visit www.regeneron.com/social-media-terms for information on how to engage with us on social media. An important note about privacy: Regeneron is committed to your privacy and will not ask for sensitive personal information such as social security number, date of birth or bank account details via email or social media.

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