ML Research Engineer Intern: Quant Finance & HPC

Jumptrading; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Jump Trading Group is seeking world-class engineers to collaborate with research, trading, and engineering teams to build state-of-the-art ML systems for quantitative finance. You will work on training pipelines on HPC clusters, low-latency inference, and production deployment across multiple languages including C, C++, Python, and CUDA.

The role emphasizes collaboration with researchers and quants, large-scale data handling, and observable, high-performance systems.

Qualifications

• Creative thinkers who are driven, self-motivated, and eager to solve challenging problems.
• Proficiency in Python and/or C++.
• Proficiency in PyTorch, JAX, TensorFlow or other DL library.
• Ability to thrive in a collaborative, team-oriented environment.
• Expertise in GPU or Accelerator programming (CUDA, Triton, SYCL, ROCm or equivalent).
• Experience building ML systems at large scale (hundreds of TBs of training data, low latency or high throughput inference requirements).
• Excellent written and verbal communication skills in English.
• Reliable and predictable availability required.

Responsibilities

• Apply state-of-the-art techniques to complex and challenging domains.
• Work closely with researchers and quants to build flexible and reusable frameworks for financial ML.
• Optimize training pipelines to make the best use of HPC resources.
• Integrate ML models into production systems where latency matters.
• Work across a mix of programming languages: C / C++ / Python / CUDA and other low-level GPU languages.
• Build large scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle time on research.
• Other duties as assigned or needed.

Skills

Python

C++

PyTorch

JAX

TensorFlow

CUDA

GPU programming

ML systems

English communication

Collaboration

Job description

Jump Trading Group is seeking world-class engineers to collaborate with research, trading, and engineering teams to build state-of-the-art ML systems for quantitative finance. You will work on training pipelines on HPC clusters, low-latency inference, and production deployment across multiple languages including C, C++, Python, and CUDA.

The role emphasizes collaboration with researchers and quants, large-scale data handling, and observable, high-performance systems.