Senior Machine Learning Research Scientist

Pfizer

Confirmed live yesterday High trust
Closes in 3 days

Quick summary

Work type
On-site
Location
Cambridge, MA
Salary
$106,000–$176,600 / yr
Employment
Full-time
Posted
5 days ago
Freshness
Confirmed live yesterday
Closes
Oct 30, 2026 (soon)

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $210k
This role $141k
$89k $263k
below market most similar roles pay here above market

This role pays less than 96% of similar roles. Most pay $174,175–$246,150 — the blue band above. At the midpoint, this role pays about $141k versus about $210k for comparable roles.

Based on 240 similar postings.

Employer

About Pfizer

Pfizer Inc. is one of the world''s largest biopharmaceutical companies, researching, developing, manufacturing, and marketing medicines and vaccines across multiple therapeutic areas including oncology, cardiology, and infectious diseases. Industry: Biopharmaceuticals

Pfizer currently has 8 open roles on FindRole.

Listed pay typically runs $122,550–$204,250 across 6 roles with salary data.

Most-posted roles

View all roles at Pfizer

At a glance

TL;DR · Senior Machine Learning Research Scientist

The Senior Machine Learning Research Scientist joins the Machine Learning and Computational Sciences group to lead independent and collaborative research in computational antibody design and optimization. This role focuses on accelerating the discovery of next-generation biologic therapeutics by developing state-of-the-art machine-learning methods for multi-objective, constraint-aware antibody optimization. The successful candidate will conduct original research in sequence- and structure-based generative modeling, leveraging NGS-derived antibody repertoires to predict developability and affinity. Key technical requirements include proficiency in Python, PyTorch, NumPy, SciPy, and scikit-learn, alongside experience with GPU acceleration and high-performance computing environments like Slurm. The work involves integrating deep learning, computational chemistry, and molecular modeling to solve complex protein science problems, ultimately translating foundational AI research into real-world drug design and impactful therapeutic solutions.

What you'll do

  • Conduct original research in computational antibody engineering using sequence- and structure-based generative modeling.
  • Develop and deploy machine-learning methods for multi-objective antibody optimization regarding affinity, stability, and developability.
  • Apply proprietary computational frameworks and models to predict antibody developability and affinity.
  • Leverage NGS-derived antibody repertoires to inform rational sequence- and structure-based design.
  • Integrate computational chemistry, molecular modeling, and deep learning to develop powerful computational solutions.
  • Communicate complex computational models and machine-learning algorithms to broad scientific audiences across diverse disciplines.
  • Identify and adopt promising external methods and tools by staying current with relevant scientific literature.
  • Publish research in high-impact journals and present findings at scientific conferences to enhance external visibility.

What we're looking for

  • Ph.D. in computational chemistry, physical or biological sciences, chemical engineering, computer science, or a related discipline.
  • Familiarity with concepts, techniques, and 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 including NumPy, SciPy, scikit-learn, and PyTorch.
  • Experience with compute-intensive machine-learning workloads, GPU acceleration, high-performance computing environments, performance debugging, and reproducible experiment management.
  • Demonstrated ability to conduct independent research and produce publication-quality scientific work.
  • Prior experience or demonstrated interest in antibody design or protein engineering (preferred).
  • Work authorization in the United States.

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