Applied ML Researcher for Trading Systems

Trading Interview; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Job summary

Jane Street is seeking smart, curious people to join our ML team and push the boundaries of trading models. You will train deep learning models powering our trading strategies while leveraging a large GPU cluster and distributed training workflows.

Our team collaborates across researchers, engineers, and traders, and you will help shape the ML landscape here—exploring LLMs, image models, RL, and classical techniques. You’ll also mentor teammates and present new ideas at conferences.

Qualifications

• Hands-on experience with empirical ML problems.
• Ability to apply logical and mathematical thinking to diverse problems.
• Intellectual curiosity and eagerness for state-of-the-art ML research across domains.
• Fluency with a versatile set of ML models and tricks.
• Hands-on coding skills in Python and ML frameworks.
• Willingness to ask questions, admit mistakes and learn new things.

Responsibilities

• Train models for the next generation of trading strategies.
• Build scalable systems and training pipelines for large models.
• Share techniques, mentor teammates, and participate in conferences.

Skills

Empirical ML problems

Logical & mathematical thinking

Curiosity & research mindset

Versatile ML models & tricks

Python and ML framework coding

Questioning & learning attitude

Job description

Jane Street is seeking smart, curious people to join our ML team and push the boundaries of trading models. You will train deep learning models powering our trading strategies while leveraging a large GPU cluster and distributed training workflows.

Our team collaborates across researchers, engineers, and traders, and you will help shape the ML landscape here—exploring LLMs, image models, RL, and classical techniques. You’ll also mentor teammates and present new ideas at conferences.