Campus ML Research Engineer (Full-Time)

Full-time ML engineering role building financial-ML frameworks, HPC training pipelines, low-latency inference, and large-scale GPU systems with Python, C++, CUDA, and modern ML libraries.

• Build reusable 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 low-level GPU technologies.
• Python and/or C++.
• PyTorch, JAX, TensorFlow, or another deep-learning library.
• GPU programming with CUDA, Triton, SYCL, ROCm, or similar tools.
• Large-scale ML systems, including very large training datasets and low-latency or high-throughput inference.
• Strong written and verbal English.
• Creativity, self-motivation, collaboration, and reliable availability.

Jump does not expect every candidate to have every listed skill. International candidates are encouraged to apply. Jump states that it sponsors work visas for full-time positions.

Details

Role information

Location London

Job type Graduate

Category Machine Learning

Company

Chicago, United States

Global quantitative trading firm combining research, advanced engineering, AI/ML, and high-performance infrastructure across markets and time horizons.

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