Campus ML Research Engineer
Jump Trading is a global trading firm where traders, engineers, and researchers develop trading strategies, models, infrastructure, and systems across asset classes and time horizons.
About Jump Trading
Jump Trading is a global trading firm focused on research-driven trading and the engineering of scalable models, tools, infrastructure, and execution systems. Its operations combine trading, technology, AI/ML, and quantitative research, and it also runs research and talent programs including conference travel grants and a fellowship program.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will collaborate with researchers, quants, and engineers to build machine learning systems for quantitative finance. You will optimize training pipelines on high-performance computing resources, integrate low-latency inference systems into production, develop large-scale ML systems, and work with C, C++, Python, CUDA, and other GPU languages.
Requirements
- Proficiency in Python and/or C++
- Proficiency in PyTorch, JAX, TensorFlow, or another deep learning library
- Expertise in GPU or accelerator programming, such as CUDA, Triton, SYCL, or ROCm
- Experience building large-scale ML systems
- Excellent written and verbal communication skills in English
- Reliable and predictable availability
Responsibilities
- Apply state-of-the-art techniques to complex domains
- Build flexible and reusable frameworks for financial ML
- Optimize training pipelines for high-performance computing resources
- Integrate ML models into production systems
- Develop large-scale ML systems
- Improve research productivity by reducing iteration cycle time
