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Chase · 19 hours ago

Machine Learning Scientist - Natural Language Processing (NLP) - Sr Associate - Machine Learning Center of Excellence

277 Park Ave, New York, NY, 10172, US

Full-time

Onsite

Mid, Senior Level

$128K/yr - $195K/yr

2+ years exp

JPMorgan Chase is a leading global financial institution that invests heavily in innovation and technology. As a Machine Learning Scientist specializing in Natural Language Processing (NLP), you will develop and deploy machine learning solutions, particularly in Generative AI, while collaborating across various business lines to drive transformational change.

BankingFinancial Services

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

Qualification

PhD in quantitative disciplineGenerative AI (GenAI)Machine learning methodsDeep learning toolkitsMathematicsStatisticsA/B experimentationCloud-native deploymentProduction-quality codeScientific thinkingCommunication skills

Required

PhD in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science, OR an MS with at least 2 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

Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences

Preferred

Strong background in Mathematics and Statistics; Familiarity with the financial services industries and continuous integration models and unit test development

Knowledge in search/ranking 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 or Deep Learning at a major conference or journal