The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

The Machine Learning Center of Excellence (MLCOE) partners across the firm to create and share Machine Learning Solutions for our most challenging business problems. Comprised of a multi-disciplinary community of experts focused exclusively on Machine Learning, the MLCOE works together to employ cutting-edge techniques in disciplines such as Deep Learning and Reinforcement Learning. 

As an AI Product Manager - Conversational AI - Executive Director in the Machine Learning Center of Excellence, you will have the unique opportunity to be a pivotal leader in our firm-wide transformational efforts to shape the future of banking. You will be partnering with senior data scientists in the MLCOE and lines of businesses to build and manage firm-wide analytics products. You will be a key leader of a cross-functional team of data scientists, engineers, architects, designers, annotators, and project managers and will have the chance to shape your product's vision, strategy, adoption, and manage ongoing stakeholder demand. You will push the boundaries of what is possible and innovate quickly in a rapidly evolving field.

For more information about the MLCOE, please visit http://www.jpmorgan.com/mlcoe.  To learn about how we're using AI/ML to drive transformational change, please read this blog: https://www.jpmorgan.com/insights/technology/technology-blog?source=cib_di_jp_aBtechblog102

Job Responsibilities

Lead strategic planning, goal-setting, and roadmap development specifically for the conversational AI product and the LLM foundational libraries Maintain a comprehensive understanding of LLM use cases across the MLCOE portfolio, facilitating connections among individuals addressing similar challenges and guiding them towards solutions that leverage reusable components or common methodologies Define and champion a strategic vision, acting as the primary evangelist for this vision and ensuring the product meets risk and control requirements Engage with senior stakeholders across various businesses (Markets, Investment Banking, Consumer Banking, etc.) and functional groups (Legal, Technology, Operations, Finance) to collect business requirements and create detailed product requirements documents Oversee and prioritize high-impact initiatives requested by stakeholders, ensuring alignment with the strategic vision Collaborate closely with technical teams to direct and oversee the planning and execution of the product roadmap and use cases Provide comprehensive updates on product and use case status to senior management and stakeholders

Required qualifications, capabilities, and skills

10+ years of experience in product management, with a proven track record of leadership and strategic impact Strong knowledge of LLM fine-tuning, hallucination detection, Q&A and NLQ techniques Strong track record of owning and developing a product domain strategy and roadmap, specifically for conversational AI and LLMs. Able to balance short-term goals and long-term vision. Must have experience capturing and analyzing requirements (internal and external) and translating them into a viable product through agile development. Able to build strong partnerships with technical teams. Deep knowledge of the data ecosystem, including data ingestion, data engineering, data quality, data orchestration, end-to-end infrastructure, usage/consumption, and data privacy considerations and governance. Comprehensive understanding of the ML workflow, spanning from annotation, model training, model serving, scoring, pre/post processing, productionization, and feedback capture

Preferred qualifications, capabilities, and skills

Proven experience in business analysis and driving operational change/system development. Able to identify critical requirements and potential gaps by understanding complex and interdependent processes.  Proven experience working with Front Office, Operations and/or in a Consulting capacity within the banking industry is a plus Knowledge of AI/ML, cloud (AWS) computing and architecture, Big Data management technologies, and ML platform tools is a plus Strong knowledge of MS tools; Excel, PowerPoint, Project, Visio, SharePoint or other collaboration tools (Figma, Lucid)  Practical knowledge of JIRA to build roadmaps