Senior AI Research Scientist - Foundation Models & Agentic AI

About the role

Wells Fargo's Model Risk Management (MRM) team is seeking a Senior Quantitative Analytics Specialist (AI Research Scientist - Foundation Models & Agentic AI - Senior AVP) to support cutting-edge applied research and development initiatives in Artificial Intelligence, with a focus on building the next generation of Foundation Models, Agentic AI solutions, and Generative AI systems. This role offers a unique opportunity to work at the intersection of AI research and real-world financial applications that impact millions of customers.

Responsibilities

• Perform highly complex research projects in AI / Generative AI / Agentic AI / Machine Learning from ideation, experimentation, implementation, evaluation, and documentation.
• Support building the next generation of foundation models and agentic AI systems through exploration, application, and rigorous evaluation of emerging AI technologies that solve real-world challenges.
• Collaborate closely with interdisciplinary teams, including researchers, data scientists, applied engineers, and domain experts.
• Translate research insights into impactful business solutions, open-source contributions, patents, and publications.
• Contribute to building the next generation of foundation models and agentic AI systems trained or operating on large volumes of heterogeneous data—both structured and unstructured—that enhance Wells Fargo's products, services, and operations.
• Publish in top-tier AI/ML conferences and journals and represent Wells Fargo in the broader AI research community.

Requirements

• 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.
• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.

Qualifications

• PhD in Computer Science, Artificial Intelligence, or a closely related computational field, or an MSc with at least 3 years of relevant applied research or industry experience.
• Solid proven research track record with publications in top-tier AI/ML conferences such as NeurIPS, ICML, ICLR, NAACL, or EMNLP, combined with a demonstrated interest in translating research into real-world applications that impact millions of customers.
• Deep expertise in one or more specialized areas, including but not limited to:
  • Foundation Models (GPT-4, BERT, LLaMA, Claude)
  • Large Language Models (LLMs)
  • Large Reasoning Models
  • Multimodal Models
  • Agentic AI
• Demonstrated ability to apply GenAI / Agentic AI in the full build lifecycle—design, implementation, testing, and iteration—leveraging AI coding copilots (e.g., GitHub Copilot) and agentic coding workflows to accelerate delivery while maintaining enterprise standards.
• Hands-on experience with GPU infrastructure, Transformer architecture, and modern AI/ML development frameworks and tools such as TensorFlow, PyTorch, Hugging Face, AWS, GCP.
• Strong engineering background with demonstrated ability to contribute to collaborative software engineering projects, including version control, code reviews, and scalable system design.
• Experience with transferring foundation models, LLMs, and agentic AI systems into production.

Pay

$139,000.00 – $260,000.00 (base pay range; may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location). Employees may also be eligible for incentive opportunities.

Schedule

This position offers a hybrid work schedule and requires willingness to work onsite at the stated location on the job posting. This position is eligible for VISA sponsorship.

Benefits

• Health benefits
• 401(k) Plan
• Paid time off
• Disability benefits
• Life insurance, critical illness insurance, and accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement