Pfizer, S.A. de C.V
Director of AI Engineering Pfizer R&D
Pfizer, S.A. de C.V, Cambridge, Massachusetts, us, 02140
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, TensorFlow) 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 colleagues. Highlights include health and disability insurance, preventative health programs, mental health support, retirement plans, paid time off, parental leave, and more.
Ethics, Transparency & Inclusion Pfizer reports payments and other transfers of value to healthcare providers as required by federal and state transparency laws (Sunshine Act). Pfizer is committed to equal opportunity in all employment decisions and complies with applicable non‑discrimination laws. This position requires permanent work authorization in the United States.
Accessibility If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com. This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process, and/or interviewing.
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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, TensorFlow) 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 colleagues. Highlights include health and disability insurance, preventative health programs, mental health support, retirement plans, paid time off, parental leave, and more.
Ethics, Transparency & Inclusion Pfizer reports payments and other transfers of value to healthcare providers as required by federal and state transparency laws (Sunshine Act). Pfizer is committed to equal opportunity in all employment decisions and complies with applicable non‑discrimination laws. This position requires permanent work authorization in the United States.
Accessibility If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com. This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process, and/or interviewing.
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