Machine Learning Scientist – Natural Language Processing; NLP – Vice President – Machine Learning

Machine Learning Scientist – Natural Language Processing (NLP) – Vice President – Machine Learning

Seattle, WA 98194

At JPMorgan Chase, AI and technology promote our global operations with unmatched scale and speed. We invest over $18 billion annually in innovation, data leverage, and security to shape the future for our clients, communities, and employees. The Chief Data & Analytics Office (CDAO) accelerates our data and analytics journey, with the Machine Learning Center of Excellence (kých) creating and deploying solutions for complex business challenges.

By ensuring data quality and leveraging insights, the CDAO supports our commercial goals, enhancing productivity and risk management through AI and machine learning and developing new products, improving productivity, and enhancing risk management effectively and responsibly.

• 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.

• PhD in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science, OR an MS with at least 3 years of industry or research experience in the field.
• Solid background in Generative AI (GenAI) and hands‑on experience with and solid understanding of machine learning and deep learning methods and toolkits (e.g., Tensor Flow, PyTorch, Num Py, 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 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.

• 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.

We offer a competitive total rewards package including base salary determined based on the после role, experience, and skill set and location. Eligible roles may receive commission‑based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity. We also offer a range of benefits and programs to meet employee needs, including comprehensive health care coverage, on‑site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching, and more.

Additional details about total compensation and benefits will be provided during the hiring process.

Base Pay / Salary:
Seattle, WA $ – $ / year;
New York, NY $ – $ / year.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We 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…