ML Research Engineer - Finance, HPC & Low-Latency

Tradermath; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Private Medical Insurance

Vision and Dental Insurance

Group Pension Scheme

Life Assurance and Income Protection

Parental Leave

Parking and Commuter Benefits

Job summary

Jump Trading Group is seeking world-class engineers to partner with research, trading, and engineering teams to build state-of-the-art ML systems for quantitative finance. You will work on training pipelines, low-latency inference, and scalable ML frameworks across C/C++, Python, and GPU languages in a fast-paced, collaborative environment.

Ideal candidates possess deep expertise in Python/C++, DL libraries, and accelerator programming, with a track record in large-scale ML deployments and

Qualifications

• Proficiency in Python and/or C++.
• Experience with PyTorch, TensorFlow or similar DL libraries.
• Ability to work in a collaborative research/trading environment.
• Expertise in GPU or accelerator programming (CUDA/Triton/SYCL/ROCm).
• Experience building ML systems at large scale with big data and low latency requirements.

Responsibilities

• Apply state-of-the-art techniques to complex ML problems.
• Collaborate with researchers and quants to build reusable ML frameworks for finance.
• Optimize training pipelines for HPC resources.
• Integrate ML models into production systems where latency matters.
• Work across C/C++, Python, and GPU languages to deliver scalable systems.
• Build observable, performant ML systems and reduce research iteration cycles.
• Perform other duties as assigned.

Skills

Python

C++

PyTorch

TensorFlow

GPU programming

Large-scale ML

English comms

Team collaboration

Tools

CUDA

Triton

SYCL

ROCm

Job description

Jump Trading Group is seeking world-class engineers to partner with research, trading, and engineering teams to build state-of-the-art ML systems for quantitative finance. You will work on training pipelines, low-latency inference, and scalable ML frameworks across C/C++, Python, and GPU languages in a fast-paced, collaborative environment.

Ideal candidates possess deep expertise in Python/C++, DL libraries, and accelerator programming, with a track record in large-scale ML deployments and