Campus ML Research Engineer (full-time)

Jump Trading Jump Trading · Quant · London, United Kingdom · Front Office

Jump Trading is seeking ML Research Engineers to build state-of-the-art ML systems for quantitative finance. Responsibilities include applying ML techniques, building frameworks, optimizing training pipelines on HPC, and integrating models into low-latency production systems. The role requires expertise in Python/C++, deep learning libraries, and GPU programming, with experience in large-scale ML systems.

What you'd actually do

  1. Apply state-of-the-art techniques to complex and challenging domains.
  2. Work closely with researchers and quants to build flexible and reusable frameworks for financial ML.
  3. Optimise training pipelines to make the best use of our HPC resources.
  4. Integrate ML models into production systems where latency matters.
  5. Build large scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle time on research.

Skills

Required

  • Python
  • C++
  • Pytorch
  • JAX
  • Tensorflow
  • GPU programming
  • CUDA
  • Triton
  • SYCL
  • ROCm
  • large scale ML systems
  • low latency inference
  • high throughput inference

Nice to have

  • ML systems
  • quantitative finance
  • HPC
  • CUDA
  • Triton
  • SYCL
  • ROCm
  • C++
  • Python

What the JD emphasized

  • low-latency inference
  • large scale ML systems
  • latency matters

Other signals

  • ML systems
  • quantitative finance
  • low-latency inference
  • HPC
  • large-scale ML systems