🚀 Internship

2023 - Machine Learning Center of Excellence Associate Program - Off-Cycle Internship - NLP, Speech & Recommender Systems Internship (London)

🚀 Off-cycle


25d left
Apply by Feb 28


Strategically positioned in the Chief Technology Office, our work spans across all of J.P. Morgan’s 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.

The successful candidate will apply sophisticated machine learning methods to a wide variety of complex domains within natural language processing, large language models, speech recognition and understanding, reinforcement learning, and recommendation systems. The candidate must excel in working in a highly collaborative environment with their MLCOE mentors, business experts and technologists in order to conduct independent research and deploy solutions into production. The candidate must have a strong passion for machine learning, solid expertise in deep learning with hands-on implementation experience, and invest independent time towards learning, researching, and experimenting with innovations in the field. 

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Area of Responsibilities



Our Off-Cycle Associate Internship Program begins in Spring, Summer or Autumn, 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 JPMorgan’s 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.
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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 2023 through August 2024Solid background in NLP, large language models, speech recognition and modelling, or personalization/recommendation. Familiarity with state-of-the-art practice in these domainsProficient 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 goalsSolid written and spoken communication to effectively communicate technical concepts and results to both technical, and business audiencesCurious, hardworking, detail-oriented and motivated by complex analytical problemsAbility to work both independently and in highly collaborative team environments Beneficial SkillsStrong background in Mathematics and StatisticsFamiliarity with the financial services industriesPublished research in areas of natural language processing, deep learning, or reinforcement learning at a major conference or journalAbility to develop and debug production-quality codeFamiliarity with continuous integration models and unit test developmentPublished research in areas of natural language processing, speech recognition, reinforcement learning, or deep learning at a major conference or journal
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