Campus ML Research Engineer (Full-Time)
Jump Trading2 months ago
London, United KingdomSenior
Responsibilities
- Apply advanced machine learning techniques to complex financial and quantitative problems.
- Collaborate with researchers, quantitative researchers, traders, and engineers to build reusable financial ML frameworks.
- Optimize ML training pipelines for high-performance computing resources.
- Integrate ML models into low-latency production systems.
- Build observable, performant, flexible large-scale ML systems and reduce research iteration cycle time.
Requirements
- Proficiency in Python and/or C++.
- Proficiency in PyTorch, JAX, TensorFlow, or another deep learning library.
- Expertise in GPU or accelerator programming with technologies such as CUDA, Triton, SYCL, or ROCm.
- Experience building large-scale ML systems involving very large training datasets or low-latency and high-throughput inference.
- Strong written and verbal communication skills in English.
- Ability to work collaboratively, solve challenging problems, and maintain reliable and predictable availability.
Benefits
- Private medical, vision, and dental insurance.
- Travel medical insurance.
- Group pension scheme.
- Group life assurance and income protection schemes.
- Paid parental leave.
- Parking and commuter benefits.
- Work visa sponsorship is available for full-time positions.
Categories
About Jump Trading
Jump Trading is a privately held quantitative and high-frequency trading firm that designs low-latency systems and models to trade global markets across asset classes, including equities, futures, options, and cryptocurrencies. It trades its own capital rather than selling software or services, and operates from Chicago with offices across North America, Europe, and Asia; the firm was founded in 1999. Affiliates include Jump Crypto for digital assets and the venture arm Jump Capital.