Quantitative Developer

About Us AXQ Capital is a global quantitative investment firm with offices in New York, Beijing, Shanghai, and Hong Kong . We pursue consistent alpha through rigorous scientific research and sustained investment in technology and data infrastructure. Our strategies are deployed across global markets, spanning multiple geographies, asset classes, and trading horizons. Responsibilities As a Quantitative Developer, you will work closely with our research and engineering teams to contribute to solutions across strategy research, systematic trading, and risk management. Working under the guidance of senior team members, your work will include: Contributing to global multi-market connectivity and cross-region, multi-asset-class data, research, backtesting, and trading systems — taking ownership of well-scoped components and growing into broader areas of the stack Helping build and maintain event-driven backtesting and simulation frameworks, with attention to consistency in data semantics and time models across research, backtesting, and production environments Implementing and improving pieces of our order management, execution, and real-time risk systems, with a focus on writing correct, well-tested, and performant code Requirements 0–3 years of software engineering experience, including internships; prior exposure to quantitative finance is a plus but not required Bachelor's degree or higher in Computer Science, Natural Sciences, Engineering, Financial Mathematics, or a related quantitative field Solid programming skills and computer science fundamentals; proficient in Python, with working knowledge of (or strong interest in learning) a statically-typed language such as C++, Rust, or Go Familiarity with Linux, basic networking, and concurrency concepts; willingness to deepen these skills on the job Curiosity, drive, and the ability to learn quickly when tackling unfamiliar problems Sense of ownership over the work you take on, and willingness to ask questions early Preferred Qualifications Internship, research, or personal project experience related to trading systems, market data, or backtesting Coursework, competitions, or open-source contributions demonstrating strong engineering or quantitative skills (e.g., ICPC, Kaggle, well-maintained GitHub projects) Effective use of AI-assisted coding tools (e.g., Claude Code, Cursor, Codex)