Senior AI/ML Engineer, Research Data AI and Predictive Modeling

Pfizer

Confirmed live 2 days ago High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Pearl River, NY
Salary
$139,100–$231,900 / yr
Posted
3 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $219k
This role $186k
$124k most similar roles pay here $279k

This role pays less than 72% of similar roles. Most pay $182,643–$254,750 — the shaded band above. At the midpoint, this role pays about $186k versus about $219k 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 27 open roles on FindRole.

Listed pay typically runs $106,000–$176,600 across 27 roles with salary data.

Most-posted roles

View all roles at Pfizer

At a glance

TL;DR · Senior AI/ML Engineer, Research Data AI and Predictive Modeling

Senior AI/ML Engineer - Research Data AI and Predictive Modeling (Vaccine R&D) is a leadership role within the Vaccines Research team focused on transforming scientific data into 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. Responsibilities include building automated ingestion pipelines, establishing semantic data frameworks, and developing knowledge graphs with RAG capabilities to power predictive modeling for immunogenicity assessment and candidate prioritization. The role requires expertise in Python, PyTorch, or TensorFlow, along with experience in cloud environments and high-performance computing. You will solve complex problems in vaccine science by integrating preclinical, clinical, and real-world data to accelerate development. Key technical areas include generative AI, foundation models, agentic systems, and multi-modal learning for scientific innovation.

What you'll do

  • Design and implement 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 machine-readable assets.
  • Establish semantic data frameworks, metadata standards, and ontologies to improve data interoperability and discoverability.
  • Build and advance knowledge graphs and retrieval systems to enable AI interaction with structured and unstructured research knowledge.
  • Deploy machine learning models using multimodal datasets to generate insights into vaccine-induced immune responses and protection mechanisms.
  • Translate strategic AI objectives into scalable technical roadmaps and implementation plans for the research organization.
  • Evaluate and implement emerging technologies including foundation models, generative AI, and agentic systems for vaccine research.
  • Mentor scientists and technical teams on AI best practices and data-centric approaches to scientific discovery.

What we're looking for

  • PhD in Computer Science, Machine Learning, Computational Biology, Software Engineering, AI, or a related discipline.
  • Master's degree and at least 4 years of applied AI/ML experience in R&D or life sciences if the candidate does not hold a PhD.
  • Proven experience architecting and implementing data-intensive AI/ML solutions using complex scientific, biological, clinical, or real-world datasets.
  • Experience transforming heterogeneous research data into scalable, reusable data products or AI-ready ecosystems.
  • Strong expertise in Python and modern AI/ML frameworks such as PyTorch or TensorFlow.
  • Experience designing data architectures, semantic data models, knowledge graphs, and metadata standards.
  • Experience working in cloud and/or high-performance computing environments.
  • Candidates must be authorized to work in the United States.

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