IMC
Quantitative Developer
About this role
IMC seeks a Quantitative Developer to bridge research and production trading systems, building infrastructure that transforms quantitative strategies into live trading edge. You'll own the complete lifecycle from backtesting and feature engineering through execution, with direct feedback on real-world impact.
What you'll do
- Build and maintain systems connecting research to production with rapid iteration cycles
- Design high-fidelity backtesting and simulation infrastructure accounting for latency and market microstructure
- Create, compute, and manage feature and signal pipelines across multiple instruments and time horizons
- Optimize trading strategies while balancing theoretical performance with real-world execution constraints
- Debug issues across the full research-to-execution pipeline
- Collaborate with research and engineering teams to refine systematic trading approaches
What they're looking for
- Python and C++ production experience
- Data analysis with pandas, polars, or similar libraries
- Probability, statistics, and time series analysis
- Backtesting and simulation framework expertise
- Machine learning applied to systematic trading strategies
- Low-latency systems development
- Cross-functional collaboration across research and engineering
- 3-7 years quantitative software development experience
Benefits
- Base salary $200,000–$225,000 USD
- Discretionary bonus
- Paid leave
- Insurance coverage
- Collaborative, high-performance culture
- Access to cutting-edge research environment
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IMC
IMC builds trading technology and financial systems powered by software, machine learning, and hardware engineering. The company is hiring interns and graduate-level engineers and researchers across software, machine learning, and hardware disciplines to develop trading algorithms, research strategies, and collaborative technology solutions.
View all jobs at IMCLikely interview questions
- Walk us through a quantitative trading system you built from research to production. What were the biggest challenges in moving from backtesting to live trading, and how did you handle them?
- Describe your experience designing backtesting or simulation infrastructure. How did you account for latency, market microstructure, and real-world constraints?