Director of AI Engineering Pfizer R&D

Where frontier AI meets world-class science to accelerate medicines to patients

Pfizer is building an AI-first R&D engineone where AI is not a support function but a core scientific capability shaping how medicines are discovered developed and delivered.

We are recruiting AI Engineers to be embedded into the various scientific disciplines of R&D including Target Discovery Medicinal and Biomedicine Design ADME (Absorption Distribution Metabolism Excretion) Translational & Genomics Medicine Clinical Manufacturing Preclinical Toxicology Clinical Trial Design & Execution Medical Functions Real World Experience Global Regulatory functions Safety and Pharmacovigilance. You will help drive the discovery and development of Pfizers next generation of breakthrough medicines.

As a Director of AI Engineering embedded within one of our core scientific disciplines youll work shoulder-to-shoulder with leading scientists and clinicians to translate complex biology into new therapies supported by AI models. Your models wont live in notebookstheyll influence molecules selected studies designed and patients treated.

If youre a rising AI technical leader (25 years post-graduate training) from a top research environment who thrives at the intersection of AI biology and real-world impact this is an opportunity to help define how AI is applied and practiced in modern medicine potentially impacting the lives of patients globally.

What youll do (you could be involved in one or more of these tasks pending your expertise and interests):

• Build AI that directly shapes R&D decisions
  Design develop and scale production-grade AI systems embedded in drug discovery and development programswhere model outputs inform choices on molecules experiments trials and patient access to clinical trials.
• Own foundational and predictive modeling end-to-end
  From molecular optimization and experimental design to clinical trial simulation patient stratification and operational forecastingtake ideas from concept through validation deployment and measurable value.
• 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: cloud and HPC environments distributed training reproducibility governance and observabilitydesigned for scientific credibility and operational scale. Automate and standardize the entire lifecycle of ML systems from initial development to long-term production maintenance providing compliance and an audit trails.
• Decode high-dimensional biology
  Integrate multimodal dataomics imaging real-world evidence and scientific literatureinto 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 defensible 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.

What youll bring

• PhD or Masters in Computer Science Machine Learning Computational Biology Software Engineering AI or a related discipline.
• AI native
• 25 years of applied AI/ML experience. Experience in life sciences preferred but not required (pharma biotech or health tech).
• A working understanding of R&D workflows is preferred but not required across target identification lead optimization translational science clinical design operations forecasting or portfolio analytics.
• Comfort operating across disciplineschemistry biology pharmacology statisticswith the ability to ground models in biological and clinical reality.
• Demonstrated expertise in predictive modeling generative AI and ML system design.
• Strong programming skills in Python and modern ML frameworks (e.g. PyTorch TensorFlow) plus experience scaling models in cloud and/or HPC environments.
• Proven ability to collaborate with other scientists and could include laboratory bench researchers clinicians product teams and business leaders.
• Clear scientific communication intellectual curiosity and a mission-driven mindset focused on improving patient outcomes.

Ready to build AI that changes patient lives

If youre excited to take ownership of high-impact AI systems work alongside exceptional scientists and help define the future of AI-driven medicine wed love to connect.

Where will you be located:

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.