Director of AI Engineering
Pfizer
full-time
Posted on:
Location Type: Hybrid
Location: Cambridge • California • Massachusetts • United States
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Job Level
Tech Stack
About the role
- 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
- From molecular optimization and experimental design to clinical trial simulation, patient stratification, and operational forecasting—take 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 observability—designed 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 data—omics, imaging, real-world evidence, and scientific 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, 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.
Requirements
- PhD or Master’s in Computer Science, Machine Learning, Computational Biology, Software Engineering, AI, or a related discipline.
- AI native 2–5 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 disciplines—chemistry, biology, pharmacology, statistics—with 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.
Benefits
- Relocation assistance may be available based on business needs and/or eligibility.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
AIMLpredictive modelinggenerative AImolecular optimizationexperimental designclinical trial simulationoperational forecastingprogramming in PythonML system design
Soft skills
collaborationscientific communicationintellectual curiositymission-driven mindsetmentoringinfluencingproblem-solvingadaptabilitycuriosityleadership
Certifications
PhD in Computer ScienceMaster’s in Computer ScienceMaster’s in Machine LearningMaster’s in Computational BiologyMaster’s in Software EngineeringMaster’s in AI