Research Scientist/Research Engineer, Reinforcement Learning

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 Benefits Discretionary bonus eligibility Medical, dental, and vision insurance HSA, FSA, and Dependent Care options Employer Paid Group Term Life and AD&D Insurance Voluntary Life & AD&D insurance Paid vacation plus paid holidays Retirement plan with employer match Paid parental leave Wellness Programs Annual Base Salary Range $200,000—$350,000 USD