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.Job ResponsibilitiesResearch and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing communityDevelop 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 systemsCollaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into productionDrive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the businessRequired Qualifications, Capabilities, and SkillsPhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data ScienceOr 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 methodsExtensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goalsPreferred Qualifications, Capabilities, and SkillsStrong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test developmentKnowledge in search/ranking, Reinforcement Learning or Meta LearningExperience 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 codePublished research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journalWe are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. #J-18808-Ljbffr