Belvedere Trading, LLC
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Machine Learning Researcher
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Belvedere Trading, LLC . Belvedere Trading is a leading proprietary trading firm headquartered in downtown Chicago, with a satellite office in Boulder, Colorado. Our teams provide liquidity to the market through market-making activities, combining expertise in commodities, interest rates, ETFs, and equity index options with advanced technology. We continually develop, optimize, and upgrade our trading models and software systems to stay competitive in a dynamic market environment. Our close collaboration with the technology team ensures ongoing improvement of our proprietary solutions. High-performance proprietary development is key to our success and competitive edge. We foster a culture driven by intellectual curiosity, aiming to innovate in trading technology and shape the future of the industry. We prioritize the development and deployment of high-performance trading software through a team-based, holistic approach. We seek passionate team members whose contributions are vital to our ongoing success. This role focuses on developing and refining self-adaptive, feedback-driven models that learn from and react to rapidly changing environments, potentially replacing or augmenting human decision-making. You will join a collaborative team of researchers and engineers working on cutting-edge ML applications in a high-impact domain. If you thrive in a fast-paced environment and enjoy solving complex challenges, we would love to hear from you. What You'll Do
Research and develop machine learning models for real-time, feedback-driven systems Manage the uncertainty inherent in the marketplace to balance risk and reward in trades Design and test adaptive algorithms capable of evolving with data and market regimes Build models that simulate or replace human decision-making in complex, uncertain systems Integrate control theory principles to enhance model stability, responsiveness, and robustness Collaborate with engineers to deploy research into production environments with real-time constraints Iterate and improve models based on system performance and market dynamics Communicate findings and methodologies clearly to researchers, engineers, and stakeholders Develop best practices for machine learning within the quantitative team What You'll Need
Ph.D. in Computer Science, Engineering, Applied Mathematics, or related field 5+ years of experience applying machine learning in feedback-loop systems, robotics, autonomous decision-making, or control systems Experience dealing with uncertainty in problem statements Strong knowledge of ML algorithms, especially reinforcement learning, online learning, or adaptive control, with deployment experience Proficiency in Python and ML libraries like PyTorch, TensorFlow, or JAX Analytical thinking and experience tackling systems-level problems Ability to work with Data Engineers to build robust data pipelines Financial market knowledge is a plus but not required Team-oriented mindset, motivated by complex, long-term problems requiring iteration Availability to work in a hybrid structure out of Chicago or Boulder offices $140,000 - $240,000 a year. Additional benefits include discretionary bonuses and various employee benefits, available on our website.
Employment may require compliance certifications during onboarding or employment. We encourage applicants from diverse backgrounds and underrepresented groups to apply, even if they do not meet all qualifications. No unsolicited resumes accepted from agencies. This position is based in Chicago or Boulder with a hybrid work structure.
Seniority level
Mid-Senior level Employment type
Full-time Job function
Other
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Machine Learning Researcher
role at
Belvedere Trading, LLC . Belvedere Trading is a leading proprietary trading firm headquartered in downtown Chicago, with a satellite office in Boulder, Colorado. Our teams provide liquidity to the market through market-making activities, combining expertise in commodities, interest rates, ETFs, and equity index options with advanced technology. We continually develop, optimize, and upgrade our trading models and software systems to stay competitive in a dynamic market environment. Our close collaboration with the technology team ensures ongoing improvement of our proprietary solutions. High-performance proprietary development is key to our success and competitive edge. We foster a culture driven by intellectual curiosity, aiming to innovate in trading technology and shape the future of the industry. We prioritize the development and deployment of high-performance trading software through a team-based, holistic approach. We seek passionate team members whose contributions are vital to our ongoing success. This role focuses on developing and refining self-adaptive, feedback-driven models that learn from and react to rapidly changing environments, potentially replacing or augmenting human decision-making. You will join a collaborative team of researchers and engineers working on cutting-edge ML applications in a high-impact domain. If you thrive in a fast-paced environment and enjoy solving complex challenges, we would love to hear from you. What You'll Do
Research and develop machine learning models for real-time, feedback-driven systems Manage the uncertainty inherent in the marketplace to balance risk and reward in trades Design and test adaptive algorithms capable of evolving with data and market regimes Build models that simulate or replace human decision-making in complex, uncertain systems Integrate control theory principles to enhance model stability, responsiveness, and robustness Collaborate with engineers to deploy research into production environments with real-time constraints Iterate and improve models based on system performance and market dynamics Communicate findings and methodologies clearly to researchers, engineers, and stakeholders Develop best practices for machine learning within the quantitative team What You'll Need
Ph.D. in Computer Science, Engineering, Applied Mathematics, or related field 5+ years of experience applying machine learning in feedback-loop systems, robotics, autonomous decision-making, or control systems Experience dealing with uncertainty in problem statements Strong knowledge of ML algorithms, especially reinforcement learning, online learning, or adaptive control, with deployment experience Proficiency in Python and ML libraries like PyTorch, TensorFlow, or JAX Analytical thinking and experience tackling systems-level problems Ability to work with Data Engineers to build robust data pipelines Financial market knowledge is a plus but not required Team-oriented mindset, motivated by complex, long-term problems requiring iteration Availability to work in a hybrid structure out of Chicago or Boulder offices $140,000 - $240,000 a year. Additional benefits include discretionary bonuses and various employee benefits, available on our website.
Employment may require compliance certifications during onboarding or employment. We encourage applicants from diverse backgrounds and underrepresented groups to apply, even if they do not meet all qualifications. No unsolicited resumes accepted from agencies. This position is based in Chicago or Boulder with a hybrid work structure.
Seniority level
Mid-Senior level Employment type
Full-time Job function
Other
#J-18808-Ljbffr