Senior Machine Learning Research Scientist

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.

(Minimum Requirements):

• Ph.D. in computational chemistry, the physical or biological sciences, chemical engineering, computer science, or a related discipline.
• Familiarity with the 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 (e.g., 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 (e.g., Slurm), performance debugging, and reproducible experiment management.
• Demonstrated ability to conduct independent research and produce publication-quality scientific work.

Bonus Points If You Have (Preferred Requirements):

• 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 (e.g., AWS, or GCP). Strong publication record and demonstrated contribution to the machine learning field.

Additional Information:

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

The annual base salary for this position ranges from $106,000.00 to $176,600.00. In addition, this position is eligible for participation in Pfizer's Global Performance Plan with a bonus target of 15.0% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life's moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site - U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.

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.