Jobs · Analyst · Missouri

Senior AI Research Scientist - Foundation Models & Agentic AI

Wells Fargo · St Louis, MO · Yesterday
Analyst$139k–$260k/yrFull-time

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—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/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.

Required qualifications

  • 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

Desired 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, 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

Hybrid work schedule; willingness to work onsite at stated location on the job posting.

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

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