Jobs / United States / Pfizer INC

Pfizer INC

Senior Principal AI Research Engineer

6 Locations Posted today

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Skills this job asks for

LLMsMachine learningData engineeringA/B testing

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 40 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Pfizer INC paid sponsored hires in similar roles2 certified filings for “SENIOR VALIDATION ENGINEER” (Industrial Engineers) in WA: $96k–$117k, median $107k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 40 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Pfizer INC paid sponsored hires in similar roles
2 certified filings for “SENIOR VALIDATION ENGINEER” (Industrial Engineers) in WA: $96k–$117k, median $107k. Most were filed at wage level I (50%) — 1 lottery entry, ≈15% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

Help Build a New AI-Native Operating Model At Pfizer, we're investing in the future of AI-enabled drug discovery. This role is about more than using AI to improve existing ways of working. We are building a new operating model in which small, highly capable teams combine human expertise with AI to achieve outcomes and move at a pace that previously required much larger organizations. We are looking for people who want to help invent and champion that model: individuals willing to rethink how work is organized, how problems are decomposed, what can be delegated to intelligent systems, and how humans and AI work together most effectively. Successful candidates will use AI not simply as a productivity tool, but as a means to fundamentally transform how scientific and technical work gets done—and will help others across R&D adopt these new ways of working. Why This Role Is Different Own Meaningful Problems You'll own critical AI capabilities from architecture through production deployment. Rather than contributing to isolated components, you'll lead the design and delivery of end-to-end systems that directly enable scientific discovery. Work Where AI Meets Real-World Impact The systems you build will support researchers tackling some of the toughest challenges in medicine, helping accelerate insights across discovery, development, and translational science. Operate at the Frontier of AI You will work across technologies and domains including: • Large Language Models (LLMs) • Agentic AI Systems • Multimodal Learning • Scientific Machine Learning • Retrieval-Augmented Generation (RAG) • Knowledge Graphs • Distributed Training and Inference • AI Platforms and MLOps • AI Evaluation and Benchmarking Accelerate Your Growth You'll work alongside experts in AI, engineering, computational biology, and drug discovery while taking on increasing technical ownership and influence. Build, Ship, Learn, Repeat We value engineers who can move from ambiguity to execution, convert ideas into working systems, measure outcomes, and continuously improve based on real-world feedback. The Opportunity As a Senior Principal AI Research Engineer, you will build the machine learning systems that transform innovative models into secure, reliable, and scalable capabilities for scientists across Pfizer. This is an intermediate-level engineering role with significant technical ownership. You will: • Own an end-to-end subsystem, platform capability, or workflow • Make sound architecture and design tradeoff decisions • Deliver production-quality software and AI solutions • Drive technical execution for complex projects • Influence engineering standards and best practices • Help less-experienced engineers grow through collaboration, code reviews, and technical coaching Success in this role requires strong engineering fundamentals, demonstrated experience delivering production systems, and the ability to operate effectively in an environment where science, technology, and business impact intersect. What You'll Do Build the AI Systems Behind Tomorrow's Scientific Breakthroughs • 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 enables AI capabilities to move beyond experimentation and into everyday scientific use Own End-to-End Technical Delivery • Translate scientific and business needs into technical solutions • Lead architecture, implementation, testing, deployment, monitoring, and continuous improvement for your area of ownership • Drive projects from concept through production and operational suppo

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