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.

Our team is a group of quantitative researchers, engineers, and ML experts leading reinforcement learning research and trading at Jump. Our mission is to combine emerging techniques and original research to learn optimal decision-making policies from financial market data and monetize them globally. We are building the future of ML-powered trading through breakthrough reinforcement learning, and we're looking for an exceptional Research Scientist/Research Engineer to join our team.

What You’ll Do

As a Research Scientist/Research Engineer working on RL, you'll be at the forefront of applying reinforcement learning to markets. You'll conduct original research and own the systems that turn it into production trading: designing and evaluating policy architectures, reward formulations, and objective horizons with rigorous out-of-sample benchmarking; partnering with trading and research teams to source, integrate, and validate their alpha signals within the RL framework; ensuring simulation fidelity against live trading by modeling market microstructure, fill dynamics, liquidity, and latency; building efficient tooling to store, process, and analyze very large volumes of market and signal data; and communicating findings to technical and trading audiences. This isn't incremental optimization; we're pushing the boundaries of what reinforcement learning can do at scale, where your improvements directly impact live trading.

Other duties as assigned or needed.

Skills You’ll Need

• 5+ years of experience developing reinforcement learning and/or deep learning systems with measurable impact in industry and/or academia
• Depth in reinforcement learning, including experience designing reward formulations, policy architectures, and evaluation, and taking RL methods from research into production
• Proficiency in Python and/or C++
• Familiarity with ML libraries/frameworks such as PyTorch (preferred), TensorFlow, and/or JAX
• Strong foundation in mathematics and statistics
• PhD or Master's degree in Computer Science, Machine Learning, Robotics (or a related subject)
• Strong publication record at ICML, ICLR, AAAI, NeurIPS, CVPR, or equivalent
• Ability to thrive in a collaborative, team-oriented environment
• Creative thinkers who are driven, self-motivated, and eager to solve challenging problems
• Reliable and predictable availability
• Excellent written and verbal communication skills in English