Applied AI ML Director - NLP / LLM and Graphs (Hiring Immediately)

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. As an Applied AI ML Director - NLP / LLM and Graphs within the Chief Data & Analytics Office, Machine Learning Centre of Excellence, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including natural language processing, graph analytics, speech analytics, time series, reinforcement learning and recommendation systems. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly collaborative environment, working together with our business, technologists and control partners to deploy solutions into production. If you have a strong passion for machine learning and enjoy investing time towards learning, researching and experimenting with new innovations in the field, this role is for you. We value solid expertise in Deep Learning with hands-on implementation experience, strong analytical thinking, a deep desire to learn and high motivation. Job Responsibilities Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as natural language processing (NLP), speech recognition and analytics, time-series predictions or recommendation systems Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community Required qualifications, capabilities, and skills PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with significant years of industry or research experience in the field. Solid background in NLP, LLM and graph analytics and hands-on experience and solid understanding of machine learning and deep learning methods Hands on experience building agentic AI / multi-agent systems within regulated or compliance-driven environments Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals, with a focus on agentic systems and LLM evaluation Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems Preferred qualifications, capabilities , and skills: Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development Knowledge in graph integration with LLM, Reinforcement Learning or Meta Learning Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment and ability to develop and debug production-quality code Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal About MLCOE The Machine Learning Center of Excellence (MCLOE) team partners across the firm to create and share Machine Learning Solutions for our most challenging business problems. In this role you will work and collaborate with a team comprised of a multi-disciplinary community of experts focused exclusively on Machine Learning. On this team you will work with cutting-edge techniques in disciplines such as Deep Learning and Reinforcement Learning For more information about the MLCOE, please visit .