Senior Machine Learning Research Scientist

Pfizer • Cambridge, MA

1d • $106,000 - $176,600 • Onsite

About The Position

Pfizer’s Machine Learning and Computational Sciences group seeks a Senior Machine Learning Scientist to lead independent and collaborative research in computational antibody design and optimization. The role develops and applies modern computational and machine-learning approaches to accelerate discovery of next-generation biologic therapeutics, translating foundational AI research into practical drug design.

The scientist will conduct research in computational antibody engineering, especially sequence- and structure-based generative modeling, and develop machine-learning methods for multi-objective antibody optimization. The work involves collaboration with computational and experimental researchers across disciplines, using computational chemistry, molecular modeling, and deep learning to address therapeutic discovery challenges. The position also contributes to scientific communication, external visibility, publications, and conference presentations.

The role is assigned on premise. Relocation support may be available. Applicants must be authorized to work in the United States by any employer; U.S. work visa sponsorship is not available.

Requirements

• Ph.D. in computational chemistry, physical or biological sciences, chemical engineering, computer science, or a related discipline.
• Familiarity with concepts, techniques, and commonly used tools for sequence analysis and protein structure modeling.
• Strong background in protein language models and structure-aware predictive and generative modeling.
• Proficiency in Python and modern scientific computing and machine-learning libraries, such as NumPy, SciPy, scikit-learn, and PyTorch, including model training and evaluation workflows.
• Experience with compute-intensive machine-learning workloads, including GPU acceleration, high-performance computing environments such as Slurm, performance debugging, and reproducible experiment management.
• Demonstrated ability to conduct independent research and produce publication-quality scientific work.
• Permanent work authorization in the United States; visa sponsorship is unavailable.

Nice To Haves

• Prior experience or demonstrated interest in antibody design or protein engineering.
• Experience fine-tuning foundation models using small and biased datasets.
• Experience training and deploying models in cloud environments such as AWS or GCP.
• Strong publication record and demonstrated contribution to the machine-learning field.

Responsibilities

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

Benefits

• 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution.
• Paid vacation, holidays, and personal days.
• Paid caregiver, parental, and medical leave.
• Medical, prescription drug, dental, and vision coverage.
• Participation in Pfizer’s Global Performance Plan, with a bonus target of 15% of base salary.
• Eligibility to participate in the share-based long-term incentive program.
• Relocation assistance may be available based on business needs and/or eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree