AI Research Scientist, Foundation Models & Agentic AI

Wells Fargo•St. Louis, MO

1d•$100,000 - $196,000•Hybrid

About The Position

Wells Fargo is hiring an AI Research Scientist for its Frontier AI Model Methodology team, which develops and implements methodologies, AI agents, and technology solutions to improve and accelerate model development and validation across the organization. The role supports applied research and development in artificial intelligence, focusing on foundation models, agentic AI solutions, and generative AI systems. It contributes tools and methodologies that enhance model governance, validation efficiency, and risk management, connecting AI research with financial applications that affect customers. The scientist supports research from ideation and experimentation through implementation, evaluation, and documentation; helps develop and rigorously evaluate foundation models and agentic systems; and collaborates with researchers, data scientists, engineers, and domain experts. The role also translates research into business solutions, open-source contributions, patents, and publications, and represents Wells Fargo in the AI research community. The position has a hybrid work schedule, with onsite work at one of the listed locations.

Requirements

At least 2 years of quantitative analytics experience, or equivalent demonstrated through work experience, training, military experience, or education.
Bachelor's degree or higher in statistics, mathematics, physics, engineering, computer science, economics, or another quantitative discipline.

Nice To Haves

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.
Research track record with publications in top-tier AI/ML conferences such as NeurIPS, ICML, ICLR, NAACL, or EMNLP, and interest in translating research into real-world applications.
Expertise in one or more areas such as foundation models, large language models, large reasoning models, multimodal models, or agentic AI.
Ability to apply generative AI and agentic AI across the full build lifecycle, including design, implementation, testing, and iteration, using AI coding copilots and agentic coding workflows while maintaining enterprise standards.
Hands-on experience with GPU infrastructure, Transformer architecture, and AI/ML frameworks and tools such as TensorFlow, PyTorch, Hugging Face, AWS, or GCP.
Strong engineering background and ability to contribute to collaborative software engineering projects, including version control, code reviews, and scalable system design.
Experience transferring foundation models, LLMs, and agentic AI systems into production.

Responsibilities

Support complex AI, generative AI, agentic AI, and machine learning research projects from ideation, experimentation, implementation, evaluation, and documentation.
Explore, apply, and rigorously evaluate emerging AI technologies for foundation models and agentic AI systems that address real-world challenges.
Collaborate with researchers, data scientists, applied engineers, and domain experts.
Translate research insights into business solutions, open-source contributions, patents, and publications.
Contribute to foundation models and agentic AI systems trained on or operating with large volumes of structured and unstructured data to enhance Wells Fargo products, services, and operations.
Publish in leading AI/ML conferences and journals and represent Wells Fargo in the broader AI research community.