The Generative AI team in Consumer Home Lending is enabling the practical application of generative AI to transform how Chase serves customers and empowers employees. We operate across three pillars: Solutions (building production-ready AI applications), Governance (ensuring responsible AI deployment), and Enablement (spreading AI capabilities throughout the organization).

As an Applied AI Vice President within our Consumer and Community Banking Home Lending Generative AI solutions team, you will play a pivotal role in developing solutions and experimenting with state-of-the-art models. You will join our dynamic team dedicated to building high-impact solutions using generative technologies. We are focused on developing a leading Generative AI program and environment that will empower our users. Our team actively collaborates with customers to develop, optimize, and support business-critical use cases, ensuring that our platform meets the evolving needs of our clients.

Job responsibilities

Serve as a subject matter expert on a wide range of Gen AI techniques and optimizations.Provide in-depth knowledge of AI models.Provide leadership and mentorship for junior team membersEnhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques.Conduct experiments using latest Generative AI technologies, analyzing results.Provide Hands on coding to bring the experimental results into production solutions by collaborating with engineering team. Owning end to end code development in python for both proof of concept/experimentation and production-ready solutions.Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks. Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions.Integrate Generative AI within the ML Platform using state-of-the-art techniques.

 

Required qualifications, capabilities, and skills

5 years + python development experience in a machine learning roleExperience of Generative AI builds, Agents and MCP.Strong background in Natural Language Processing (NLP) and Large Language Models (LLMs)Hands-on experience with machine learning and deep learning methods.Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow; embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search).Ability to work on tasks and projects through to completion with limited supervision.Passion for detail and follow through. Excellent communication skills and team player

 

Preferred qualifications, capabilities, and skills

Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods.Experience of all LLM models and their capabilitiesExperience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc.