Machine Learning Researcher

Jane Street; Hong Kong; On-site; HKD 223,200 - 279,000; Full time

Job summary

A financial technology firm based in Hong Kong is seeking a Machine Learning Researcher intern to work closely with experienced researchers on innovative ML projects. Candidates should be PhD students or postdocs with strong empirical ML backgrounds and a passion for solving complex problems. This role offers hands-on experience in applying cutting-edge techniques to real-world trading strategies, requiring proficiency in Python and various ML frameworks. The ideal candidate will be curious and eager to learn in a collaborative environment.

Qualifications

• You should be a PhD student or postdoc working on empirical ML research 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.

Responsibilities

• Work closely on projects with experienced ML Researchers.
• Conduct an end-to-end study of an unexplored dataset.
• Tuning hyperparameters, debugging training issues, or analyzing model predictions.

Skills

Empirical ML research

Logical and mathematical thinking

Python programming

State-of-the-art ML techniques

Curiosity and problem-solving

Fluency in English

Education

PhD student or postdoc

Tools

Python ML frameworks

Job description

About the Position

Our goals are to give you a real sense of what it’s like to work at Jane Street full time as a Machine Learning Researcher, and a truly unparalleled educational experience. You’ll work side by side with experienced ML Researchers on projects that we’ve selected for their combination of novel ML ideas and relevance to real-world systematic trading strategies. You'll learn how we think about markets through challenging classes and activities, and practice using established methods alongside our own unique twists to train practical models.

At Jane Street, the lines between research, technology, and trading are intentionally blurry. As our strategies grow more sophisticated, close collaboration is essential for continuing to push the boundaries of what’s possible. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing thousands of high-end GPUs. Trading poses unusual challenges—large models and nonstationary datasets in a competitive multi-agent environment—that force us to search for novel techniques.

You’ll spend the bulk of your internship working closely on projects with experienced ML Researchers at Jane Street. You might conduct an end-to-end study of an unexplored dataset, try a new modeling paradigm for a thorny problem, or consider blue-sky approaches that we’re still trying to figure out. The problems we work on rarely have clean, definitive answers, and they often require insights from colleagues across the firm with different areas of expertise. Depending on the day, you might be diving deep into market data, tuning hyperparameters, debugging training issues, or analyzing the predictions your model makes.

Note that given the IP-sensitive nature of machine learning research at Jane Street, it is unlikely that any research findings associated with the internship will be suitable for outside academic publication.

About You

If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here. If you have a curious mind and a passion for solving interesting problems, we have a feeling you’ll fit right in. You should be:

• A PhD student or postdoc working on empirical ML research problems, or someone with equivalent research experience
• 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 drawn from many problem domains
• Fluent with a versatile set of models and tricks
• Able to rapidly implement and iterate on your ideas in Python and your favorite ML framework
• Eager to ask questions, admit mistakes, and learn new things
• Fluent in English

If you’d like to learn more, you can read about our interview process and meet some of the team. Learn more about Jane Street’s internship program here.

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