Machine Learning Center of Excellence (Quant AI) Summer Associate

JPMorgan Chase

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Work type
On-site
Location
Palo Alto, CA
Employment
Full-time
Posted
2 days ago
Freshness
Confirmed live today

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Similar $199k
$139k $272k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $151,836–$246,271.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1240 open roles on FindRole.

Listed pay typically runs $153,591–$207,500 across 14 roles with salary data.

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At a glance

TL;DR · Machine Learning Center of Excellence (Quant AI) Summer Associate

As a 2027 Machine Learning Center of Excellence (Quant AI) - Summer Associate, you will join the Machine Learning Center of Excellence within the Chief Data & Analytics Office. You will work alongside technologists and researchers to explore cutting-edge research and apply machine learning techniques to unique data assets. Your daily responsibilities include researching new methods through independent study and experimentation, developing state-of-the-art models to solve real-world problems, and collaborating with various partner teams to deploy production solutions. You must possess deep knowledge in Machine Learning, Data Mining, Applied Mathematics, Optimization, and Statistics. Required technical skills include C/C++, Python, or JAVA, along with experience using TensorFlow, PyTorch, or JAX. You will address complex business problems by designing experiments and training frameworks for high-performance computing environments.

What you'll do

  • Research and explore new machine learning methods through independent study and experimentation.
  • Develop state-of-the-art machine learning models to solve real-world business problems.
  • Apply advanced machine learning techniques to the firm's unique data assets.
  • Design experiments and training frameworks to evaluate model performance against business goals.
  • Collaborate with cross-functional teams to deploy machine learning solutions into production.
  • Communicate technical concepts and results to both technical and business audiences.
  • Utilize machine learning toolkits and ETL pipelines for batch and real-time data processing.

What we're looking for

  • Enrolled in a PhD or MS program in Computer Science, Physics, Mathematics, Engineering, or a related quantitative field.
  • Expected graduation date between December 2027 and August 2028.
  • Solid programming skills in C/C++, Python, JAVA, or other equivalent languages.
  • Deep knowledge in Machine Learning, Data Mining, Applied Mathematics, Optimization, and Statistics.
  • Knowledge of machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, JAX) and ETL pipelines.
  • Ability to design experiments, training frameworks, and evaluate model performance metrics aligned with business goals.
  • Solid written and spoken communication skills to convey technical concepts to technical and business audiences.
  • Interest in quantitative finance and/or portfolio management (preferred).

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