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Director of AI Engineering Pfizer R&D

Job in Cambridge, Middlesex County, Massachusetts, 02140, USA
Listing for: Pfizer, S.A. de C.V
Full Time position
Listed on 2026-01-13
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 150000 - 180000 USD Yearly USD 150000.00 180000.00 YEAR
Job Description & How to Apply Below

United States – Massachusetts – Cambridge
We’re in relentless pursuit of breakthroughs that change patients’ lives. We innovate every day to make the world a healthier place.

Overview

Pfizer Research & Development is building an AI‑first R&D engine—where AI is a core scientific capability shaping how medicines are discovered, developed, and delivered. We are recruiting AI Engineers to be embedded in scientific disciplines such as Target Discovery, Medicinal Design, ADME, Translational & Genomics Medicine, Clinical Manufacturing, Preclinical Toxicology, Clinical Trial Design & Execution, Medical Functions, Real World Experience, Global Regulatory, Safety, and Pharmacovigilance.

As a Director of AI Engineering, you will collaborate with leading scientists and clinicians to translate complex biology into new therapies, supported by AI models that influence molecules selected, studies designed, and patients treated.

Responsibilities
  • Build AI that directly shapes R&D decisions. Design, develop, and scale production‑grade AI systems embedded in drug discovery and development programs—where model outputs inform choices on molecules, experiments, trials, and patient access to clinical trials.
  • Own foundational and predictive modeling end‑to‑end. Take ideas from concept through validation, deployment, and measurable value in areas such as molecular optimization, experimental design, clinical trial simulation, patient stratification, and operational forecasting.
  • Advance generative AI for drug design. Apply state‑of‑the‑art generative approaches to molecular and protein engineering, prototype quickly, evaluate rigorously, and deploy responsibly in high‑stakes scientific contexts.
  • Engineer elegant, reliable ML systems. Architect robust pipelines with modern MLOps—including cloud and HPC environments, distributed training, reproducibility, governance, and observability—to meet scientific credibility and operational scale.
  • Decode high‑dimensional biology. Integrate multimodal data—omics, imaging, real‑world evidence, and literature—into representations that surface biological insight and guide experimental and clinical strategy.
  • Influence portfolio and strategy decisions. Partner with scientific and strategy leaders to model uncertainty, run scenario analyses, and optimize resource allocation across a complex R&D portfolio.
  • Stay at the frontier. Continuously assess emerging AI methods and tools, translating advances into practical applications for a specific R&D discipline.
  • Raise AI fluency across the organization. Mentor scientists and engineers, foster hands‑on curiosity, and help build a culture where rigorous experimentation and learning are the norm.
  • Represent the science externally. Publish, present, and engage with the broader AI and life‑sciences community at leading conferences and forums.
Qualifications
  • PhD or Master’s in Computer Science, Machine Learning, Computational Biology, Software Engineering, AI, or a related discipline.
  • AI native, with 2–5 years of applied AI/ML experience. Experience in life sciences preferred, but not required.
  • Working understanding of R&D workflows preferred.
  • Comfort operating across disciplines—chemistry, biology, pharmacology, statistics.
  • Demonstrated expertise in predictive modeling, generative AI, and ML system design.
  • Strong programming skills in Python and modern ML frameworks (e.g., PyTorch, Tensor Flow) with experience scaling models in cloud and/or HPC environments.
  • Proven ability to collaborate with scientists and other stakeholders.
  • Clear scientific communication, intellectual curiosity, and mission‑driven mindset focused on improving patient outcomes.
Location

We are fostering an on‑site environment for maximal colleague interactions at one of our major innovation hubs, including Kendall Sq, Cambridge, MA;
La Jolla, CA;
Bothell/Seattle, WA.

Work Location Assignment

This is a hybrid role requiring you to live within commuting distance and work on‑site an average of 2.5 days per week. Relocation assistance may be available based on business needs and/or eligibility.

Benefits

Pfizer offers competitive compensation and benefits programs designed to meet the diverse needs of our…

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