Senior AI Research Engineer

Pfizer • San Diego, CA

3d • $106,000 - $176,600 • Hybrid

About The Position

Pfizer is investing in AI-enabled drug discovery and developing an AI-native operating model in which small teams combine human expertise with AI to accelerate scientific and technical work. The Senior AI Research Engineer builds machine learning systems that turn innovative models into secure, reliable, and scalable capabilities for scientists across Pfizer. The role owns an end-to-end subsystem, platform capability, or workflow; makes architecture and design decisions; delivers production-quality software and AI solutions; drives complex technical work; and contributes to engineering standards while supporting less-experienced engineers.

The engineer designs, develops, and deploys production-grade AI systems supporting multimodal biomedical models and intelligent agents. Work may span data pipelines, retrieval and knowledge systems, evaluation frameworks, inference services, and human-in-the-loop workflows. The role partners with AI scientists, computational biologists, data engineers, and platform teams to turn prototypes into reusable, maintainable systems for everyday scientific use.

Responsibilities extend from translating scientific and business needs into technical solutions through architecture, implementation, testing, deployment, monitoring, operational support, and continuous improvement. The engineer balances performance, scalability, cost, reliability, security, privacy, maintainability, and delivery speed; strengthens responsible AI practices; defines success metrics; and helps teams adopt AI confidently at scale.

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 position is eligible for Pfizer's Global Performance Plan, with a 15% bonus target, and for participation in the share-based long-term incentive program. Relocation assistance may be available based on business needs and eligibility. Candidates must be authorized to work in the U.S. by any employer; U.S. work visa sponsorship is not available.

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 HPC environments.
• Ability to develop maintainable, testable, and scalable software.
• Strong proficiency in Python software development.
• Strong proficiency in modern machine learning frameworks such as PyTorch or JAX.
• Strong proficiency in software architecture and system design.
• Strong proficiency in APIs, testing, debugging, version control, and technical documentation.
• Strong proficiency in 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 less-experienced teammates.
• Must be authorized to be employed in the U.S. by any employer; U.S. work visa sponsorship is not available.
• The role requires permanent work authorization in the United States.

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.
• Engineer data pipelines, retrieval systems, evaluation frameworks, knowledge systems, inference services, and human-in-the-loop workflows.
• Create scalable software that moves AI capabilities from experimentation into everyday scientific use.
• Translate scientific and business needs into technical solutions.
• Lead architecture, implementation, testing, deployment, monitoring, operational support, and continuous improvement for areas of ownership.
• Drive projects from concept through production.
• Partner with AI scientists, computational biologists, data engineers, and platform teams.
• Transform prototypes into reusable, reliable, and maintainable systems with clear interfaces, measurable performance, and long-term sustainability.
• Balance performance, scalability, cost, reliability, security, privacy, maintainability, and speed of delivery in engineering decisions.
• Strengthen model evaluation, observability, reproducibility, lineage, security, and operational resilience.
• Implement practices that support responsible and trustworthy AI deployment in scientific environments.
• 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, technical 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

• Participation in Pfizer's Global Performance Plan with a bonus target of 15% of base salary.
• Eligibility to participate in a share-based long-term incentive program.
• 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.
• Relocation assistance may be available based on business needs and/or eligibility.

What This Job Offers

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