AI Research Scientist

US Bank; Minneapolis (MN); On-site; USD 150,000 - 210,000; Full time

Job summary

U.S. Bank seeks an AI Scientist to join the AI CoE, advancing the bank's AI strategy through applied research, rapid prototyping, and enterprise deployment.

This role spans the full AI lifecycle from exploratory research to production-grade solutions, blending scientific rigor with practical engineering. You will stay current with academic and industry advances and collaborate across teams to deliver scalable AI capabilities.

Qualifications

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Computational Linguistics, or a related field strongly preferred.
• Deep expertise in machine learning, deep learning, neural networks, transformer architectures, and foundation models.
• Experience with generative AI technologies, including LLMs, fine‑tuning, RAG systems, model evaluation, and inference optimization.
• Experience building and evaluating agentic AI systems, multi‑agent workflows, AI orchestration frameworks, and autonomous decision‑making architectures.

Responsibilities

• Monitor, evaluate, and experiment with emerging AI technologies and industry trends, focusing on generative AI and LLMs.
• Rapidly transform research concepts into working prototypes and production-ready solutions across the full lifecycle.
• Develop solutions leveraging foundation models, retrieval-augmented generation, fine-tuning, and agentic workflows.
• Partner with engineers and product teams to transition prototypes into production environments and ensure scalable deployment.

Skills

ML & DL expertise

Transformer architectures

Foundation models

RAG & agentic AI

Cross-functional collaboration

Education

Bachelor's degree in a quantitative field such as statistics, computer science, engineering or applied mathematics, or equivalent work experience

Tools

PyTorch

Job description

At U.S. Bank, we're on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at-all from Day One.

Job Description

U.S. Bank is seeking an AI Scientist to join the Artificial Intelligence Center of Excellence (AI CoE), a high-impact organization responsible for advancing the bank's AI strategy through applied research, innovation, rapid prototyping, and enterprise deployment.

This role is ideal for a highly technical and hands-on AI practitioner who thrives at the intersection of research, experimentation, and implementation. The successful candidate will continuously evaluate emerging advances in artificial intelligence, identify opportunities to create business value, rapidly prototype novel solutions, and help evolve successful concepts into scalable enterprise capabilities.

Unlike traditional data science roles, this position spans the full AI research and development lifecycle. The ideal candidate combines strong scientific and engineering expertise with a practical mindset, enabling them to move seamlessly from exploratory research and experimentation to the development and deployment of production‑grade AI solutions.

The candidate is expected to remain actively engaged with the broader AI community, stay current on academic and industry developments, and contribute to advancing AI innovation within the bank.

Key Responsibilities

AI Research & Innovation

Monitor, evaluate, and experiment with emerging AI technologies, research breakthroughs, and industry trends, with particular emphasis on generative AI, large language models (LLMs), multimodal AI, and agentic AI systems. Identify opportunities to apply advanced AI techniques to complex business problems across financial services. Conduct original AI research and exploratory investigations to assess the feasibility and value of novel approaches. Develop hypotheses, design experiments, evaluate results, and communicate findings to technical and business stakeholders. Contribute to patents, technical publications, whitepapers, prototypes, and innovation initiatives.

Prototyping & Solution Development

Rapidly transform research concepts into working prototypes and proof-of-concepts. Design, develop, and validate AI solutions across the full lifecycle, from data preparation and modeling through deployment and monitoring. Build experimental and production‑ready solutions using modern AI/ML tools, frameworks, and cloud platforms. Apply best practices in model evaluation, benchmarking, explainability, security, and responsible AI.

Generative AI & Agentic Systems

Develop solutions leveraging foundation models, generative AI, retrieval‑augmented generation (RAG), fine‑tuning techniques, and agentic workflows. Design and evaluate AI agents, multi‑agent systems, orchestration frameworks, tool‑use architectures, memory systems, and human‑in‑the‑loop workflows. Contribute to best practices for prompt engineering, model adaptation, evaluation, observability, and governance of LLM‑based systems. Assess emerging model architectures and determine their applicability within a highly regulated environment.

Deployment & Technical Collaboration

Partner with software engineers, platform teams, product managers, and business stakeholders to transition successful prototypes into production environments. Contribute to deployment and operationalization efforts for AI solutions. Help balance innovation, scalability, security, compliance, and operational requirements throughout solution development. Share knowledge and provide technical guidance to peers and junior team members. Take ownership of assigned initiatives and ensure successful delivery of AI capabilities from concept through deployment.

Basic Qualifications

• Bachelor's degree in a quantitative field such as statistics, computer science, engineering or applied mathematics, or equivalent work experience
• Eight or more years of relevant experience

Preferred Qualifications

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Computational Linguistics, or a related field strongly preferred.
• Deep expertise in machine learning, deep learning, neural networks, transformer architectures, and foundation models.
• Experience with generative AI technologies, including LLMs, fine‑tuning, RAG systems, model evaluation, and inference optimization.
• Experience building and evaluating agentic AI systems, multi‑agent workflows, AI orchestration frameworks, and autonomous decision‑making architectures.
• Hands‑on experience with Py