AI/ML Engineer - Vaccines Modeling and Antigen Discovery
Pfizer
July 01, 2026
Remote friendly (Pearl River, NY)
United States
Clinical Research and Development
Responsibilities:
- Develop predictive and multimodal models of vaccine-induced immune responses (humoral, cellular, systems immunology, durability).
- Advance translational modeling connecting preclinical, clinical, epidemiological, and real-world evidence for dose selection, patient stratification, correlates of protection, and clinical study design.
- Apply foundation models, generative AI, structure-aware learning, protein language models, and sequence-to-function modeling to identify, optimize, and prioritize novel vaccine antigens.
- Integrate computational antigen design with experimental feedback loops to improve immunogenicity, breadth, manufacturability, developability, and translational relevance.
- Build AI-ready vaccine R&D data foundations (data standards, metadata, ontologies, QC, provenance, governance, reusable data products).
- Design and responsibly deploy agentic AI workflows for scientific reasoning, literature synthesis, knowledge management, experimental planning, model interpretation, and decision traceability.
- Mentor scientists and engineers to raise AI fluency and promote responsible adoption.
Qualifications:
- PhD in CS/ML/Computational Biology/Software Engineering/AI (or related) OR Master’s plus 2+ years applied AI/ML experience in Vaccines R&D or related discovery environment.
- Working knowledge of vaccine R&D workflows (immune-response modeling, antigen discovery/optimization, translational science).
- Experience translating preclinical immunogenicity/efficacy/systems-biology readouts into clinically relevant predictions.
- Cross-functional experience across immunology, molecular biology, serology, bioinformatics, and data science.
- Expertise in foundation model and predictive modeling, generative AI, and ML system design.
- Strong Python and modern ML frameworks (e.g., PyTorch, TensorFlow); experience scaling in cloud and/or HPC.
- Collaboration experience with experimental scientists and clinicians.
Benefits/Work location/Application:
- Hybrid: live within commuting distance; on-site ~2.5 days/week.
- Annual base salary range: $106,000.00–$176,600.00; eligible for bonus (15%) and long-term incentives; comprehensive benefits (401(k), paid leave, health coverage).
- Relocation assistance may be available.
- U.S. work authorization required; no U.S. work visa sponsorship for this role.
- Develop predictive and multimodal models of vaccine-induced immune responses (humoral, cellular, systems immunology, durability).
- Advance translational modeling connecting preclinical, clinical, epidemiological, and real-world evidence for dose selection, patient stratification, correlates of protection, and clinical study design.
- Apply foundation models, generative AI, structure-aware learning, protein language models, and sequence-to-function modeling to identify, optimize, and prioritize novel vaccine antigens.
- Integrate computational antigen design with experimental feedback loops to improve immunogenicity, breadth, manufacturability, developability, and translational relevance.
- Build AI-ready vaccine R&D data foundations (data standards, metadata, ontologies, QC, provenance, governance, reusable data products).
- Design and responsibly deploy agentic AI workflows for scientific reasoning, literature synthesis, knowledge management, experimental planning, model interpretation, and decision traceability.
- Mentor scientists and engineers to raise AI fluency and promote responsible adoption.
Qualifications:
- PhD in CS/ML/Computational Biology/Software Engineering/AI (or related) OR Master’s plus 2+ years applied AI/ML experience in Vaccines R&D or related discovery environment.
- Working knowledge of vaccine R&D workflows (immune-response modeling, antigen discovery/optimization, translational science).
- Experience translating preclinical immunogenicity/efficacy/systems-biology readouts into clinically relevant predictions.
- Cross-functional experience across immunology, molecular biology, serology, bioinformatics, and data science.
- Expertise in foundation model and predictive modeling, generative AI, and ML system design.
- Strong Python and modern ML frameworks (e.g., PyTorch, TensorFlow); experience scaling in cloud and/or HPC.
- Collaboration experience with experimental scientists and clinicians.
Benefits/Work location/Application:
- Hybrid: live within commuting distance; on-site ~2.5 days/week.
- Annual base salary range: $106,000.00–$176,600.00; eligible for bonus (15%) and long-term incentives; comprehensive benefits (401(k), paid leave, health coverage).
- Relocation assistance may be available.
- U.S. work authorization required; no U.S. work visa sponsorship for this role.