Senior Machine Learning Research Scientist

Pfizer Inc.; Cambridge (MA); On-site; USD 106,000 - 177,000; Full time

Benefits offered by this job

401(k) matching

Retirement contribution

Paid vacation

Holidays & leave

Medical insurance

Prescription drugs

Dental coverage

Vision coverage

Job summary

Pfizer's MLCS group seeks a Senior Machine Learning Scientist to lead computational antibody design and optimization. You will develop advanced ML methods, apply them to predict developability and affinity, and collaborate with diverse researchers to translate AI innovations into biologic therapeutics.

You will publish and present findings, stay current with literature, and contribute to advancing Pfizer’s mission to develop breakthrough biologics.

Qualifications

• Ph.D. in computational chemistry, physical or biological sciences, chemical engineering, computer science, or related with 0+ years experience.
• Familiarity with sequence analysis and protein structure modeling.
• Strong background in protein language models and structure-aware predictive and generative modeling.
• Proficiency in Python and ML libraries (NumPy, SciPy, scikit-learn, PyTorch) including model training/evaluation.
• Experience with compute-intensive ML workloads, GPU acceleration, HPC environments (e.g., Slurm), debugging, and reproducible experiments.
• Proven ability to conduct independent research and produce publication-quality work.

Responsibilities

• Lead independent and collaborative research in computational antibody design and optimization.
• Develop and apply ML methods for multi-objective antibody optimization balancing affinity, stability, and developability.
• Apply computational frameworks to predict antibody developability and affinity.
• Leverage NGS-derived repertoires for design guidance.
• Collaborate across disciplines to integrate computational chemistry, molecular modeling, and AI advances.
• Publish and present findings in high-impact journals and conferences.

Skills

Sequence analysis

Protein structure modeling

Protein language models

Generative modeling

Independent research

Education

Ph.D. in computational chemistry or related field

Tools

Python

NumPy

SciPy

scikit-learn

PyTorch

Slurm

Job description

Use Your Power for Purpose

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.

Role Summary

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.

What You Will Achieve

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.

Here Is What You Need (Minimum Requirements)

• Ph.D. in computational chemistry, the physical or biological sciences, chemical engineering, computer science, or a related discipline with 0+ years of experience.
• 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.

• 401(k) plan with Pfizer Matching Contributions
• an additional Pfizer Retirement Savings Contribution
• paid vacation
• holiday and personal days
• paid caregiver/parental and medical leave
• medical
• prescription drug
• dental
• 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.

Sunshine Act

Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.

EEO & Employment Eligibility

Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status.

Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA.

Pfizer is an E-Verify employer.

This position requires permanent work authorization in the United States.

Pfizer endeavors to make www.pfizer.com/careers accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email [e-mail] . This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned.

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 .