Senior Principal ML Scientist - Biomedical AI Frontier

Pfizer; Groton (CT); Hybrid; USD 139,000 - 232,000; Full time

Benefits offered by this job

401(k) matching

Retirement savings contribution

Paid vacation

Job summary

Pfizer is seeking a Senior Principal Machine Learning Scientist to develop and advance AI methods for biomedical research across the drug discovery and development lifecycle. You will own model components, benchmarks, evaluation frameworks, and research workflows, collaborating with AI researchers, computational biologists, engineers, and domain experts to translate findings into trusted capabilities.

You will design rigorous experiments, build scalable evaluation standards, and create reusable

Qualifications

• PhD plus 2+ years in ML/AI or related quantitative field preferred.
• Master's degree with 5+ years of relevant industry or research experience.
• Proven ability to develop, extend, or evaluate ML methodologies on hard problems.
• Designing rigorous experiments and hypothesis-driven investigations.
• Translating research insights into meaningful outcomes for patients.

Responsibilities

• Develop Frontier AI methods for biomedical research.
• Design and execute rigorous experiments.
• Set the evaluation standard at scale.
• Translate models into scientific evidence.
• Build reusable foundation components and workflows.
• Raise the scientific bar and contribute to reviews.

Skills

Python

PyTorch

JAX

Experiment design

Education

PhD in relevant field

Master's degree in related field

Tools

Python

PyTorch

JAX

Job description

Pfizer is seeking a Senior Principal Machine Learning Scientist to develop and advance AI methods for biomedical research across the drug discovery and development lifecycle. You will own model components, benchmarks, evaluation frameworks, and research workflows, collaborating with AI researchers, computational biologists, engineers, and domain experts to translate findings into trusted capabilities.

You will design rigorous experiments, build scalable evaluation standards, and create reusable