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 incenting 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 organizations 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.

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 monetization process.

We believe that successful research efforts require a fluid mix of skills including AI/ML expertise, engineering pragmatism, statistics, and market intuition.

What You'Ll Do

: Apply state-of-the-art techniques to complex and challenging domains. Work closely with researchers and quants to build flexible and reusable frameworks for financial ML. Optimize training pipelines to make the best use of our HPC resources.

Integrate ML models into production systems where latency matters. Work across a mix of programming languages: C / C++ / Python / CUDA and other low-level GPU languages. Build large-scale ML systems that are observable, performant, and flexible.

Help improve productivity by reducing the iteration cycle time on research. Other duties as assigned or needed. g.

transformers, SSMs) Solid development skills in Python and/or C++ Familiarity with ML libraries/frameworks such as PyTorch, JAX, and/or TensorFlow 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 Bonus Points: Experience with HPC and distributed large model training Experience with GPU performance optimization (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. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions. The estimated base salary for this role (annualized) is $300,000 per year.

Campus AI Research Engineer - Deep Learning (Intern)