Campus AI/ML Researcher (Spring 2026 / Fall 2026)

About Jump Trading Group

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 incentivizing 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.

Who Should Apply?

• We are seeking researchers 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 ML expertise, engineering pragmatism, statistics, and market intuition.
• No prior knowledge of finance or trading is necessary. We’ll give you the training that you’ll need.
• Other duties as assigned or needed.

Skills You'll Need

• Creative thinkers who are driven, self-motivated, and eager to solve challenging problems with a pragmatic outlook.
• Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research.
• Familiarity with ML libraries/frameworks such as PyTorch, TensorFlow, and/or JAX.
• Proficiency in Python and/or C++.
• Ability to thrive in a collaborative, team-oriented environment.
• Ability to reason through quantitative problems and communicate effectively with trading researchers.
• Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g., transformers, SSMs).
• Reliable and predictable availability.

If you have outstanding skills in math, ML, and programming, and you are curious about the challenge of improving research with daily feedback from competitive markets, we hope you’ll apply.