Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivising collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organisations and universities to solve problems.
Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.
What you will do:
We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetisation process. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, statistics and market intuition.
Other duties as assigned or needed.
Skills You’ll Need:
- Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research
- Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs)
- Solid development skills in Python and/or C++
- Familiarity with ML libraries/frameworks such as PyTorch, TensorFlow, and/or JAX
- Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
- Ability to thrive in a collaborative, team-oriented environment
- Ability to reason through quantitative problems and communicate effectively with trading researchers
- Reliable and predictable availability required
Bonus Points
- Experience with HPC and distributed large model training
- Experience with GPU performance optimisation (CUDA or ROCm)
- Experience with end-to-end model development
- Strong opinions on best practices in ML research, tooling, and/or infrastructure
INTERNATIONAL STUDENTS are encouraged to apply.