Machine Learning Scientist - Natural Language Processing (NLP) - Vice President - Machine Learning Center of Excellence

Job Responsibilities

• Research and develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks involving Generative AI (GenAI)
• Act as a thought partner for JPMC leaders and help the business identify and implement new machine learning methods that deliver impact
• Drive cross-functional collaboration with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production
• Lead firm-wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business

Required Qualifications, Capabilities, And Skills

• PhD in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science with at least 3 years of experience OR an MS with at least 5 years of industry or research experience in the field
• Solid background in Generative AI (GenAI) and hands-on experience and solid understanding of machine learning and deep learning methods and 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 goals
• Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
• Strong written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences

Preferred Qualifications, Capabilities, And Skills

• Strong background in Mathematics and Statistics
• Familiarity with the financial services industries and continuous integration models and unit test development
• 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 or Deep Learning at a major conference or journal