Senior Machine Learning Research Scientist

At Pfizer, our purpose is to deliver breakthroughs that transform patients' lives. Central to this mission is our Research and Development team, which strives to convert advanced science and cutting-edge technologies into impactful therapies and vaccines. Whether you are engaged in discovery sciences, ensuring drug safety and efficacy, or supporting clinical trials, your role is crucial. You will leverage innovative design and process development capabilities to expedite the delivery of top-tier medicines to patients globally.

Pfizer’s Machine Learning and Computational Sciences (MLCS) group is seeking a Senior Machine Learning Scientist to lead independent and collaborative research in computational antibody design and optimization. This position focuses on developing and applying modern computational and machine-learning approaches to accelerate the discovery of next-generation biologic therapeutics. Positioned at the intersection of machine learning, protein science, and therapeutic discovery, the role is ideal for candidates eager to translate foundational AI research into real-world drug design. It offers the opportunity to join an innovative, collaborative environment that supports professional growth through mentorship, knowledge sharing, and the freedom to pursue impactful science.

In this role, you will:

• →Conduct original research in computational antibody engineering, with an emphasis on sequence- and structure-based generative modeling.
• →Develop and deploy state-of-the-art machine-learning methods for multi-objective, constraint-aware antibody optimization that balances affinity, stability, and developability.
• →Apply proprietary computational frameworks and machine-learning models to predict antibody developability and affinity.
• →Leverage NGS-derived antibody repertoires to inform sequence- and structure-based rational design.
• →Collaborate with computational and experimental researchers across diverse scientific disciplines to identify challenges and opportunities and integrate computational chemistry, molecular modeling, and AI—particularly recent advances in deep learning—to rapidly develop powerful computational solutions.
• →Communicate and explain computational models and machine-learning algorithms to broad scientific audiences across diverse disciplines.
• →Stay current with the relevant scientific literature and proactively identify, evaluate, and adopt promising external methods and tools.
• →Enhance Pfizer’s external visibility and reputation for scientific excellence through publications in high-impact journals and presentations at scientific conferences.

• Work Location Assignment: On Premise
• Relocation support available
• Last Day to Apply: October 29. 2026

Relocation assistance may be available based on business needs and/or eligibility.

Candidates must be authorized to be employed in the U.S. by any employer.

U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.