Quantitative Researcher

To support advanced quantitative research initiatives, the full-time Quantitative Finance Researcher will build environments, evaluations, and agents for systematic decision-making, working remotely or from locations including San Francisco, London, or New York. Key responsibilities Develop environments that simulate realistic market mechanics and operational constraints for quantitative research Design and implement evaluations and reward systems that accurately assess agent performance and avoid biases Manage production loops that ensure robust monitoring and failure attribution across models and data Required qualifications Depth of knowledge in reinforcement learning, agents, or post-training systems Experience in systematic trading, market microstructure, or financial simulation is beneficial but not mandatory Hands-on experience in building and debugging model-training and evaluation systems Proficiency in Python and the ability to create reusable artifacts for research purposes Demonstrated ability to tackle ambiguous problems and maintain communication with stakeholders