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Pearl River, New York, United States
Hybrid
Not Available
POSITION SUMMARY
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. The scientific value lies not within individual datasets, but in the ability to connect, contextualize, and operationalize information across these modalities.
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. These capabilities will power next-generation predictive and translational models that inform vaccine design, candidate prioritization, and decision-making across the research portfolio.
WHAT YOU"LL DO
Lead Research Data AI-Readiness strategy and Implementation
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 that improve interoperability, discoverability, and reuse.
Build and advance knowledge graphs, retrieval systems, and graph-RAG capabilities that enable scientists and AI systems to interact effectively with both structured and unstructured research knowledge.
Partner with enterprise data and digital organizations to ensure alignment with broader R&D data standards, platforms, and AI initiatives.
Advance Predictive and Translational Modeling
Develop and deploy machine learning approaches that leverage linked multimodal datasets to generate insights into vaccine-induced immune responses and mechanisms of protection.
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 to improve scientific understanding and accelerate vaccine development.
Technical Leadership and Cross-functional Influence
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 a key liaison between Vaccines Research and broader Pfizer R&D AI, data, and digital communities, ensuring vaccine-specific needs are represented while leveraging enterprise capabilities whenever possible.
Advance AI Adoption and Scientific Innovation
Evaluate and implement emerging AI technologies, including foundation models, agentic AI systems, multimodal learning approaches, and generative AI capabilities relevant to vaccine research.
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 and contribute to shaping the future of AI-enabled R&D.
MINIMUM QUALIFICATIONS
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 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 to working effectively across scientific, computational, and technology organizations.
Experience influencing technical direction and driving initiatives across cross-functional teams.
PREFERRED QUALIFICATIONS
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.
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.

Candidates must be authorized to be employed in the U.S. by any employer.
U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.

Sunshine Act
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EEO & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.
Pfizer endeavors to make www.pfizer.com/careers accessible to all users. 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. Requests for any other reason will not be returned.
To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.

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