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Machine Learning Research Engineer Internship - 2027 [New York]

Quantbot · Prop trading · New York · $190k · Posted 2026-08-11

Apply now → Applications go to Quantbot's own site.

Quantbot Technologies is a leading global quantitative investment firm deploying systematic strategies across asset classes. At the heart of our approach is large-scale research powered by advanced computing infrastructure and petabytes of comprehensive market and historical data. We combine rigorous scientific methods with modern statistical and machine learning techniques to discover, test, and implement novel investment ideas.

As a Machine Learning Research Engineering Intern, you will gain hands-on experience in designing and evaluating machine learning systems that support quantitative research. You will work alongside experienced researchers and engineers, learning how to build scalable pipelines, process large datasets, and apply state-of-the-art ML methods to real-world problems in systematic investing. This internship is designed to give you exposure to both practical engineering challenges and research-driven exploration in machine learning for quantitative finance.

Who Should Apply

Program Details
This 10-week program runs from June to August, offering training and support with a dedicated mentor. Successful interns may receive full-time job offers.

Our Culture
Join a global team that values a relaxed, collaborative environment. Enjoy company outings, traditional Friday lunches, and a focus on work-life balance. Quantbot is committed to fostering an inclusive workplace where all employees can thrive. Join us for a dynamic opportunity to grow with a pioneering quant firm and acquire skills for your future career.

Quantbot is an Equal Opportunity Employer and we do not discriminate based on race, color, religion, national origin, sex or sexual orientation, physical or mental disability, or age.

The annual base pay for this role is expected to be between $180,000 and $200,000 which will be prorated based on internship start and end date. The expected base pay range is based on information at the time this post was generated. Actual compensation for the successful candidate will be determined based on a variety of factors such as skills, qualifications and experience and level of education.

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