Machine Learning Research - 2027 Summer Internship

Tum International Gmbh; Greater London; Hybrid; GBP 20,000 - 27,000; Full time

Job summary

Jane Street offers a Summer Internship in Machine Learning Research for 2027. You will work alongside experienced ML researchers on projects blending novel ML ideas with real-world trading relevance.

The program includes hands-on dataset studies, modelling experiments, and collaboration across teams. Ideal candidates are undergraduates, PhD students, or postdocs with ML experience, strong mathematical thinking, and a passion for learning.

Qualifications

• An undergraduate, PhD student, or postdoc with practical experience working on ML problems.
• Interested in applying logical and mathematical thinking to all kinds of problems.
• Curious about the machine learning landscape and excited to apply state-of-the-art techniques.
• Fluent with a versatile set of models and tricks.
• Able to rapidly implement and iterate on your ideas in Python and your favourite ML framework.
• Eager to ask questions, admit mistakes, and learn new things.

Responsibilities

• Work closely with full-time machine learning researchers on projects selected for their novel ML ideas and relevance to real-world trading strategies.
• Conduct end-to-end studies of unexplored datasets and test new modelling paradigms.
• Iterate on models, tune hyperparameters, and analyze predictions with colleagues across the firm.

Skills

ML problems

Python

Analytical thinking

Education

Undergrad/PhD student or postdoc

Job description

Machine Learning Research - 2027 Summer Internship

Our goals are to give you a real sense of whatit's like to work at Jane Street as a MachineLearning Researcher while also providing a trulyunparalleled educational experience. You'llwork side by side with experienced ML Researcherson projects that we've selected for theircombination of novel ML ideas and relevance toreal-world systematic trading strategies.You'll learn how we think about marketsthrough challenging classes and activities, andpractice using established methods alongside ourown unique twists to train practical models.

At Jane Street, the lines between research,technology, and trading are intentionally blurry,and you’ll have access to petabytes of data, acomputing cluster with hundreds of thousands ofcores, and a growing GPU cluster containing tensof thousands of high-end GPUs. Trading posesunusual challenges—large models and nonstationarydatasets in a competitive multi-agentenvironment that force us to search for noveltechniques.

You'll spend the bulk of your internshipworking closely with full-time machine learningresearchers on projects drawn from their own work.You might conduct an end-to-end study of anunexplored dataset, try a new modelling paradigmfor a thorny problem, or consider blue-skyapproaches that we're still trying to figureout. The problems we work on rarely have clean,definitive answers, and they often requireinsights from colleagues across the firm withdifferent areas of expertise. Depending on theday, you might be diving deep into market data,tuning hyperparameters, debugging training issues,or analysing the predictions your model makes.

Note that given the IP-sensitive nature ofmachine learning research at Jane Street, it isunlikely that any research findings associatedwith the internship will be suitable for outsideacademic publication.

About you

If you've never thought about a career infinance, you're in good company. Many of uswere in the same position before working here. Ifyou have a curious mind and a passion for solvinginteresting problems, we have a feeling you'llfit right in. We're more interested in how youthink and learn than what you currently know. Youshould be:

• An undergraduate, PhD student, or postdocwith practical experience working on ML problems
• Interested in applying logical andmathematical thinking to all kinds of problems
• Curious about the machine learninglandscape and excited to apply state-of-the-arttechniques drawn from many problem domains
• Fluent with a versatile set of models andtricks
• Able to rapidly implement and iterate onyour ideas in Python and your favourite MLframework
• Eager to ask questions, admit mistakes,and learn new things

If you'd like to learn more, you can readabout our interview process, meet some of theteam, and learn more about Jane Street'sinternship program on our website.

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