AI/ML Engineer - Vaccine Research

We are looking to identify AI/ML Engineers - Vaccine Research who will play a strategic role at the intersection of artificial intelligence, vaccinology, and translational science.

You will help define the future of AI-driven vaccinology, with the potential to impact human lives globally.

Embedded within Vaccines R&D, supporting viral and bacterial vaccine programs, you will help define how advanced AI methods are applied to unlock new biological insights and accelerate next-generation vaccine innovation.

As an AI Science Engineer, you will work shoulder-to-shoulder with leading Scientists, Immunologists, and Clinicians to translate complex biology into differentiated vaccine strategies. Your work will go beyond proof‑of‑concept models - your AI systems will directly inform scientific hypotheses, experimental design, and portfolio decisions across the vaccine pipeline.

What you’ll do:

Shape scientific strategy with AI

• Design, develop, and deploy AI systems directly influence vaccine discovery and development decisions, informing antigen selection, experimental prioritization, translational strategies, and clinical study design.
• Serve as scientific thought partner to vaccine R&D leaders, helping integrate AI-driven insights into program-level and portfolio-level strategy

Own foundational and predictive modeling end-to-end

• Lead AI initiatives spanning antigen discovery and optimization, experimental design, translational modeling, clinical trial simulation, patient stratification, and operational forecasting
• Take models from concept through validation, deployment, and measurable scientific impact.

Advance generative AI for vaccine design

• Apply state-of-the-art generative and foundation models to protein and antigen engineering.
• Rapidly prototype, rigorously evaluate, and responsibly deploy AI methods in high-stakes scientific contexts.

Engineer robust, scalable AI systems

• Architect reliable ML pipelines using modern MLOps practices across cloud and HPC environments, with strong attention to reproducibility, governance, and scientific credibility
• Standardize and automate the ML lifecycle, enabling long-term sustainability, compliance, and auditability.

Decode high-dimensional biology and stay at the scientific frontier

• Integrate multimodal datasets – including omics, immunological data, clinical and real-world evidence, and scientific literature - to uncover biological insight and guide experimental and clinical decision-making.

• Continuously assess emerging AI methods and technologies, translating cutting-edge advances into practical, defensible applications for vaccine research.

Elevate AI fluency across the organization and represent Pfizer science externally

• Mentor Scientists and Engineers, foster scientific curiosity, and help build a culture where AI-enabled experimentation and learning are embedded in daily R&D practice.
• Publish, present, and engage with the broader AI, immunology, infectious disease, and vaccine/life-sciences community at leading scientific conferences and forums.

What you’ll bring

• PhD in Computer Science, Machine Learning, Computational Biology, Software Engineering, AI, or a related discipline OR
• Master’s degree in Computer Science, Machine Learning, Computational Biology, Software Engineering, AI, or a related discipline and a minimum of 2 years of applied AI/ML experience in a Vaccines R&D, Life Sciences or other related discovery focused environment
• Working knowledge of vaccine R&D workflows, including target identification, antigen design and optimization, translational science, clinical development, or portfolio analytics.
• Experience operating fluently across disciplines - molecular biology, systems immunology, pharmacology, and statistics – grounding AI models in biological and clinical reality.
• Demonstrated expertise in foundation model, 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.
• Experience collaborating with Experimental Scientists, Clinicians, and cross-functional partners.
• Clear scientific communicator with intellectual curiosity and a mission-driven mindset focused on improving patient outcomes

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.

The annual base salary for this pos