Senior AI/ML Engineer - Research Data AI and Predictive Modeling (Vaccine R&D)

Vaccines Research is seeking a highly innovative and technically accomplished AI/ML Engineering leader to accelerate the transformation of scientific data into a strategic asset for AI-driven vaccine discovery and development. This role sits at the intersection of artificial intelligence, data engineering, and vaccine science. Embedded within Vaccines Research and supporting viral/bacterial vaccine programs, the successful candidate will lead implementation of a modern AI-ready research data ecosystem that enables advanced analytics, predictive modeling, generative AI applications, and agentic scientific workflows. Vaccine research generates exceptionally diverse data, including antigen and pathogen sequences, immunological assays, omics datasets, imaging data, laboratory workflows, electronic lab notebooks, and study metadata. You will partner closely with Scientists, Bioinformaticians, Digital teams, and enterprise stakeholders to establish data foundations that make research data discoverable, interoperable, reusable, and AI-ready.

Responsibilities

Lead Research Data AI-Readiness strategy and Implementation; Advance Predictive and Translational Modeling; Technical Leadership and Cross-functional Influence; Advance AI Adoption and Scientific Innovation; Drive implementation of Vaccines Research's strategy for transforming diverse research data assets into scalable, AI-ready resources; Design and establish integrated data architectures that connect heterogeneous scientific datasets across laboratory, preclinical, and clinical domains; Develop automated data ingestion, transformation, and orchestration pipelines that convert fragmented research data into standardized, machine-readable assets; Define and implement semantic data frameworks, metadata standards, ontologies, and knowledge representations; Build and advance knowledge graphs, retrieval systems, and graph-RAG capabilities; Partner with enterprise data and digital organizations to ensure alignment with broader R&D data standards, platforms, and AI initiatives; Develop and deploy machine learning approaches that leverage linked multimodal datasets; Apply AI and predictive modeling techniques to support vaccine candidate evaluation, immunogenicity assessment, translational research, and portfolio decision-making; Advance approaches that integrate preclinical, clinical, epidemiological, and real-world datasets; Translate strategic AI objectives into scalable technical roadmaps, architectures, and implementation plans; Serve as a technical leader and trusted partner across immunology, microbiology, bioinformatics, clinical research, digital, and data science organizations; Identify opportunities to modernize research workflows through AI-enabled automation and intelligent data integration; Act as key liaison between Vaccines Research and broader Pfizer R&D AI, data, and digital communities; Evaluate and implement emerging AI technologies, including foundation models, agentic AI systems, multimodal learning approaches, and generative AI capabilities; Mentor scientists and technical teams in AI best practices, responsible AI adoption, and data-centric approaches to scientific discovery; Represent Vaccines Research in cross-functional AI initiatives

Requirements

PhD in Computer Science, Machine Learning, Computational Biology, Software Engineering, AI, or a related discipline; Master’s degree in Computer Science, Machine Learning, Computational Biology, Software Engineering, AI, or a related discipline and a minimum of 4 years of applied AI/ML experience in R&D, Life Sciences or other related discovery focused environment; Proven experience architecting and implementing data-intensive AI/ML solutions utilizing complex scientific, biological, clinical, or real-world datasets; Experience transforming heterogeneous research data into scalable and reusable data products, platforms, or AI-ready ecosystems; Strong expertise in Python and modern AI/ML frameworks such as PyTorch, TensorFlow, or equivalent technologies; Experience designing data architectures, data integration frameworks, semantic data models, metadata standards, knowledge graphs, or related technologies; Experience working in cloud and/or high-performance computing environments; Strong collaboration and communication skills with experience working effectively across scientific, computational, and technology organizations; Experience influencing technical direction and driving initiatives across cross-functional teams

Nice to have

Experience with data standards/ontology frameworks common in life sciences (e.g., FAIR data principles); Experience working with immunology, systems biology, multi-omics, flow cytometry, imaging, vaccine, or infectious disease datasets; Experience with generative AI, retrieval-augmented generation (RAG), agentic AI, foundation models, or biological foundation models; Knowledge of translational modeling, biomarker development, clinical data science, or real-world evidence applications; Record of scientific publications, patents, open-source contributions, or recognized technical leadership in AI and life sciences

Benefits

Eligibility for participation in Pfizer’s Global Performance Plan with a bonus target of 17.5% of the base salary; Eligibility to participate in share based long term incentive program; 401(k) plan with Pfizer Matching Contributions; Additional Pfizer Retirement Savings Contribution; Paid vacation, holiday and personal days; Paid caregiver/parental and medical leave; Health benefits including medical, prescription drug, dental and vision coverage; Relocation assistance may be available based on business needs and/or eligibility