2026 Machine Learning Center of Excellence (NLP) - Summer Associate
2026 Machine Learning Center of Excellence (NLP) - Summer Associate
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Job Description
The Machine Learning Center of Excellence (MLCOE) is a world-class machine learning team which continually advances state-of-the-art methods to solve a wide range of real-world financial problems using the companys vast and unique datasets. Strategically positioned in the Chief Technology Office our work spans across all of J.P. Morgans lines of business including Corporate & Investment Banking Asset Wealth Management Consumer & Community Banking and through every part of the organization from front office sales and trading to operations technology finance and more. With this unparalleled access to the firm this role offers a unique opportunity to explore novel and complex challenges that could profoundly transform how the firm operates.
As a Summer Associate within the MLCOE you will apply sophisticated machine learning methods to a diverse range of complex domains including natural language processing large language models speech recognition and understanding reinforcement learning and recommendation systems. You will collaborate closely with MLCOE mentors business experts and technologists conducting independent research and deploying solutions into production. A strong passion for machine learning solid expertise in deep learning with hands-on implementation experience and a commitment to continuous learning and innovation are essential. This role offers a unique opportunity to contribute to and learn from a world-class machine learning more about our MLCOE team at Summer Associate Internship Program begins in June depending on your academic calendar. Your professional growth and development will be supported throughout the internship program via project work related to your academic and professional interests mentorship an engaging speaker series with our senior leaders and more. Your project will have direct impact on JPMorgans businesses will be integrated into our product pipelines or be part of published research in top AI/ML conferences. Full-time employment offers may be extended upon successful completion of the program within our hybrid work model.
Job responsibilities
- Research and explore new machine learning methods through independent study attending industry-leading conferences experimentation and participating in our knowledge sharing community
- 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
Required qualifications capabilities and skills
- Enrolled in a PhD or MS in a quantitative discipline e.g. Computer Science Electrical Engineering Mathematics Operations Research Optimization Data Science or related fields or equivalent research or industry experience
- Expected graduation date of December 2026 through August 2027
- Solid background in NLP large language models speech recognition and modelling or personalization/recommendation. Familiarity with state-of-the-art practice in these domains
- Proficient in Python and experience with machine learning and deep learning toolkits (e.g. TensorFlow PyTorch NumPy Scikit-Learn Pandas)
- Scientific thinking ability to design experiments and training frameworks and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
- Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
- Ability to work both independently and in highly collaborative team environments
Preferred qualifications capabilities and skills
- Strong background in Mathematics and Statistics
- Familiarity with the financial services industries
- Published research in areas of natural language processing deep learning or reinforcement learning at a major conference or journal
- Ability to develop and debug production-quality code
- Familiarity with continuous integration models and unit test development
- Published research in areas of natural language processing speech recognition reinforcement learning or deep learning at a major conference or journal
Required Experience:
IC
Employment Type
Full-Time
