ML Research Engineer – Financial ML & Low-Latency GPU

Amsterdam Quant Society; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

Jump Trading, a global quantitative trading firm, is seeking a full-time ML engineer in London. The role focuses on building financial-ML frameworks, training pipelines, and low-latency inference on large GPU systems using Python, C++, CUDA and modern ML libraries.

The position emphasizes HPC training, observable systems, and production integration. International candidates are welcome; visa sponsorship is available. Strong English and collaboration are essential.

Qualifications

• Build reusable ML frameworks for financial applications.
• Optimise training pipelines for HPC environments.
• Integrate ML models into latency-sensitive production systems.
• Develop large-scale, observable ML systems.
• Work with Python, C++, CUDA and GPU technologies.

Responsibilities

• Build reusable ML frameworks for financial machine learning.
• Optimise training pipelines for high-performance computing.
• Integrate ML models into latency-sensitive production systems.
• Build large-scale, observable ML systems.
• Work with C, C++, Python, CUDA and other GPU technologies.

Skills

Python

C++

CUDA

GPU programming

PyTorch

JAX

TensorFlow

English communication

Education

Graduate degree in CS/ML

Tools

CUDA toolkit

Job description

Jump Trading, a global quantitative trading firm, is seeking a full-time ML engineer in London. The role focuses on building financial-ML frameworks, training pipelines, and low-latency inference on large GPU systems using Python, C++, CUDA and modern ML libraries.

The position emphasizes HPC training, observable systems, and production integration. International candidates are welcome; visa sponsorship is available. Strong English and collaboration are essential.