Senior AI Research Engineer

Pfizer • Bothell, WA

3d • Hybrid

About The Position

Pfizer is building an AI-enabled operating model for drug discovery, in which small, capable teams combine human expertise with AI to accelerate scientific and technical work. The Senior AI Research Engineer will build machine-learning systems that turn innovative models into secure, reliable, and scalable capabilities for scientists across Pfizer. The role owns meaningful AI capabilities from architecture through production deployment and supports research across discovery, development, and translational science.

The engineer will own an end-to-end subsystem, platform capability, or workflow; make architecture and design decisions; deliver production-quality software and AI solutions; and drive technical execution for complex projects. The role partners with AI scientists, computational biologists, data engineers, and platform teams to turn research prototypes into reusable, reliable, maintainable systems. It also contributes to engineering standards and supports less-experienced colleagues through collaboration, code reviews, technical coaching, and mentorship.

The position involves designing and deploying systems such as multimodal biomedical models, intelligent agents, data pipelines, retrieval and knowledge systems, evaluation frameworks, inference services, and human-in-the-loop workflows. Engineers balance performance, scalability, cost, reliability, security, privacy, maintainability, and delivery speed, while strengthening responsible AI practices, observability, reproducibility, lineage, and operational resilience. Success is measured through improvements to system performance, reliability, usability, and scientific impact.

This is a hybrid role. Colleagues must live within commuting distance of a Pfizer location and work on site an average of 2.5 days per week. The annual U.S. base salary range is $106,000 to $176,600. The role is eligible for Pfizer’s Global Performance Plan, with a 15% bonus target, and for a share-based long-term incentive program. Relocation assistance may be available depending on business needs and eligibility. Candidates must have permanent U.S. work authorization; visa sponsorship is not available now or in the future.

Requirements

• PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related technical discipline, with demonstrated experience building software, systems, or machine-learning solutions; or a master's degree with at least 2 years of relevant experience; or a bachelor's degree with at least 4 years of relevant experience.
• Demonstrated experience designing and delivering production software or machine-learning systems.
• Experience owning technical solutions from architecture through deployment.
• Experience building reliable systems in cloud, distributed-computing, or high-performance-computing environments.
• Experience developing maintainable, testable, and scalable software.
• Strong proficiency in Python software development.
• Proficiency with modern machine-learning frameworks such as PyTorch or JAX.
• Proficiency in software architecture and system design.
• Proficiency in APIs, testing, debugging, version control, and technical documentation.
• Proficiency with containers, orchestration, CI/CD, and deployment workflows.
• Depth in one or more of the following: distributed GPU training; model serving and inference optimization; AI platforms and MLOps; data and knowledge systems; LLM and agentic architectures; retrieval systems and RAG; AI evaluation frameworks; performance and infrastructure optimization.
• Ability to work effectively across interdisciplinary teams, navigate ambiguity, solve complex problems, communicate technical concepts to broad audiences, influence decisions through expertise and execution, and support and develop less-experienced teammates.
• Permanent work authorization in the United States; U.S. work visa sponsorship is not available.

Nice To Haves

• Experience in life sciences, healthcare, biotechnology, or highly regulated industries.
• Experience with multimodal AI, scientific machine learning, computational biology, or cheminformatics.
• Experience implementing responsible AI practices, evaluation frameworks, and governance controls.
• Evidence of technical impact through deployed systems, publications, patents, open-source contributions, or reusable engineering platforms.

Responsibilities

• Design, develop, and deploy production-grade AI systems supporting multimodal biomedical models and intelligent agents.
• Build data pipelines, retrieval systems, evaluation frameworks, knowledge systems, inference services, and human-in-the-loop workflows.
• Create scalable software that moves AI capabilities beyond experimentation and into everyday scientific use.
• Own an end-to-end subsystem, platform capability, or workflow, including architecture, implementation, testing, deployment, monitoring, and continuous improvement.
• Translate scientific and business needs into technical solutions and drive projects from concept through production and operational support.
• Partner with AI scientists, computational biologists, data engineers, and platform teams to transform prototypes into reusable, reliable, and maintainable systems.
• Make sound engineering tradeoffs involving performance, scalability, cost, reliability, security, privacy, maintainability, and delivery speed.
• Strengthen model evaluation, observability, reproducibility, lineage, security, and operational resilience to support responsible and trustworthy AI deployment.
• Contribute to architecture reviews, code reviews, engineering standards, and reusable technical patterns.
• Troubleshoot complex problems and improve engineering quality across the organization.
• Guide and support less-experienced engineers through collaboration, code reviews, coaching, and mentorship.
• Define success metrics and operational indicators, and continuously improve performance, reliability, usability, and scientific impact.
• Help teams adopt AI with confidence and scale.

Benefits

• 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution.
• Paid vacation, holiday, and personal days.
• Paid caregiver, parental, and medical leave.
• Medical, prescription drug, dental, and vision coverage.
• Eligibility to participate in Pfizer’s Global Performance Plan with a 15% bonus target.
• Eligibility to participate in a share-based long-term incentive program.
• Relocation assistance may be available based on business needs and/or eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior