below marketmost similar roles pay hereabove market
This role pays less than
72%
of similar roles. Most pay
$179,475–$254,750
— the blue band above.
At the midpoint, this role pays about
$186k
versus about
$217k
for comparable roles.
Based on 240 similar postings.
Employer
About Pfizer
Pfizer Inc. is one of the world''s largest biopharmaceutical companies, researching, developing, manufacturing, and marketing medicines and vaccines across multiple therapeutic areas including oncology, cardiology, and infectious diseases. Industry: Biopharmaceuticals
Pfizer currently has
8 open roles
on FindRole.
Listed pay typically runs
$122,550–$204,250
across 6 roles with salary data.
Senior AI/ML Engineer - Research Data AI and Predictive Modeling (Vaccine R&D) joins the Vaccines Research team to transform scientific data into strategic assets for vaccine discovery. You will lead the implementation of an AI-ready research data ecosystem, designing integrated architectures to connect heterogeneous datasets including antigen sequences, omics, and imaging data. Daily responsibilities involve developing automated ingestion pipelines, establishing semantic data frameworks, and building knowledge graphs and retrieval systems. You will deploy machine learning approaches to generate insights into immune responses and accelerate vaccine development. Required skills include Python, PyTorch, or TensorFlow, along with experience in cloud environments and high-performance computing. The role solves the challenge of operationalizing fragmented, multimodal research data to power next-generation predictive models and agentic scientific workflows within the vaccine research portfolio.
Design and establish integrated data architectures to connect heterogeneous scientific datasets across laboratory, preclinical, and clinical domains.
Develop automated data ingestion, transformation, and orchestration pipelines to convert fragmented research data into standardized, machine-readable assets.
Define and implement semantic data frameworks, metadata standards, and ontologies to improve data interoperability and discoverability.
Build and advance knowledge graphs, retrieval systems, and graph-RAG capabilities for interacting with structured and unstructured research knowledge.
Develop and deploy machine learning approaches to generate insights into vaccine-induced immune responses and mechanisms of protection.
Apply predictive modeling techniques to support vaccine candidate evaluation, immunogenicity assessment, and portfolio decision-making.
Translate strategic AI objectives into scalable technical roadmaps, architectures, and implementation plans.
Evaluate and implement emerging AI technologies, including foundation models, agentic AI systems, and generative AI capabilities for vaccine research.
What we're looking for
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 environments.
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.