Job Description
What You’ll Be Doing
- Build and maintain infrastructure that connects research workflows to live trading systems
- Develop high-fidelity simulation and backtesting frameworks that account for latency, market microstructure, and real-world constraints
- Design and manage feature pipelines across multiple instruments, time horizons, and market regimes
- Own the lifecycle of signals and features from research through execution
- Partner closely with researchers to optimize strategies for real-world performance
- Debug and troubleshoot issues across the full stack
- Continuously improve systems to enable faster iteration and more robust deployment of ideas
What They’re Looking For
- 3–7 years of experience in quantitative development, ideally within a trading firm or systematic environment
- Strong programming skills in Python and C++, with experience building production-grade systems
- Deep familiarity with data analysis tools (pandas, polars, or similar)
- Solid foundation in probability, statistics, and time series analysis
- Experience with backtesting, simulation, and research infrastructure
- Understanding of machine learning concepts applied to systematic strategies
- Exposure to low-latency or performance-critical systems is a plus
- Ability to operate across both research and engineering functions
Why This Role
- End-to-end ownership: See your work go from idea to production to impact
- Real collaboration: Work directly with researchers and traders, not in silos
- Technical depth: Build systems that matter in a performance-critical environment
- High visibility: Direct line of sight into how your work drives trading outcomes
- Growth opportunity: Join a team actively building and evolving its platform
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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