Software Engineer

Profitable market-maker and systematic prop trading firm is looking to add a Quantitative Developer/Software Engineer with Machine Learning experience.

This is an opportunity to join a lean, research-driven trading environment where engineering directly impacts pricing, execution, risk, and strategy performance.

The firm is already established, profitable, and scaling, with strong infrastructure in place and a mandate to hire people who can own problems end-to-end rather than sit in a narrow engineering lane.

Compensation starts at $400,000 base and can reach $850K through bonus / PnL-linked upside.

The role can be worked on a hybrid basis from New York, Chicago, or Miami

Role Includes:

• Build and optimize low-latency trading systems, research infrastructure, and ML-driven tools used directly in market making
• Develop predictive models, data pipelines, and statistical frameworks to improve pricing, execution, and microstructure signal extraction
• Work closely with quantitative researchers, traders, and developers to take ideas from research through production
• Design scalable systems for market data, backtesting, simulation, risk, and real-time trading decision-making

Must Have:

• Strong software engineering background with experience in Python and/or C++
• Exposure to machine learning, statistical modeling, or predictive analytics
• Internship or full-time experience in systematic trading, market making or low-latency environment
• Academic background in computer science, mathematics, statistics, physics, engineering, or a similarly quantitative field
• Ability to work on complex systems, move quickly, and collaborate closely with research and trading teams

This is best suited for someone who wants to sit at the intersection of engineering, machine learning, and live trading, with the ability to see their work impact real markets directly.