What you'll do
- Research and develop machine learning models for real-time, closed-loop systems with feedback
- Embrace the uncertainty persistent in the marketplace to balance the risk-reward in each individual trade
- Design and test adaptive algorithms capable of evolving with incoming data and shifting regimes
- Build models that simulate or replace human decision-making in complex, uncertain systems
- Integrate control theory principles to improve model stability, responsiveness, and robustness
- Collaborate with engineers to deploy research into production environments with real-time constraints
- Continuously iterate and improve models based on system performance and market dynamics
- Communicate findings and methodologies clearly with other researchers, engineers, and stakeholders
- Develop best machine learning practices for larger quantitative group
What you'll need
- Ph.D. in Computer Science, Engineering, Applied Mathematics, or a related quantitative field
- 5+ years of experience applying machine learning in feedback-loop systems, robotics, autonomous decision-making, or control systems
- Familiarity in dealing with uncertainty in problem statements
- Strong knowledge of machine learning algorithms, especially in reinforcement learning, online learning, or adaptive control, with practical experience deploying ML models in production
- Solid programming skills in Python (preferred), and experience with ML libraries like PyTorch, TensorFlow, or JAX
- Strong analytical thinking and a track record of tackling open-ended, systems-level problems
- Demonstrated ability to work with Data Engineers to deliver robust data pipelines
- Financial market knowledge is a plus, but not required (we value technical depth and research excellence first and foremost)
- Active team player motivated by a fast-paced environment and conviction to focus on difficult, long-duration problems that require iteration
- Availability to work in a hybrid structure out of our Chicago or Boulder offices
Top Skills
What We Do
In March of 2002, Belvedere Trading emerged as Chicago’s newest market maker, soon to join the ranks of the Windy City’s elite proprietary trading firms. Armed with printouts of Excel workbooks and a team of eager minds, Belvedere established their place in the SPX pit on the floor of the Chicago Board Options Exchange. From the beginning, we have iteratively invested in our proprietary technology and made a commitment to building our software systems from the ground up. Due to our ultramodern proprietary technology and risk management capabilities, Belvedere is able to quickly capitalize on inefficiencies in the marketplace. Our trading models and software systems are continually re-engineered, optimized, and maintained to stay on top of the industry. Building and nurturing a strong culture is one of Belvedere’s highest priorities, and we are always looking for the best and brightest talent to help us in our continued success.
Why Work With Us
At Belvedere, our differences are what allow us to compete and succeed at the highest level. Our Culture Committee and Women’s Initiative elevate the voices of our teammates to further promote an inclusive workplace. It is our priority to foster a sense of community and belonging for each team member while supporting individual development.
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Belvedere Trading Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.