9 hours ago
Hong Kong, Hong KongIntern
Responsibilities
- Develop and optimize low-latency trading systems, market data engines, and strategy backtesting frameworks.
- Implement high-performance data structures and algorithms for core modules.
- Explore and integrate agentic AI and LLM tools for strategy research, code generation, and research workflows.
- Collaborate with quantitative researchers and traders to translate strategy logic into efficient, robust code.
- Write technical documentation and build reusable components and tooling.
Requirements
- Pursuing a bachelor’s or master’s degree in computer science or a related field.
- Strong C++ fundamentals, including C++17 or later, the STL, memory management, and template programming.
- Solid understanding of data structures, algorithms, and time and space complexity analysis.
- Comfort working in a Linux development environment.
- Hands-on experience with agentic AI and LLM applications.
- Preferred: competitive programming achievements or strong contest rankings, including ICPC, CCPC, Codeforces 2000+ or equivalent, USACO, NOI/NOIP, or similar.
- Preferred: experience with quantitative projects such as strategy backtesting, high-frequency trading systems, or market data engines.
- Preferred: familiarity with multithreading, concurrency, lock-free data structures, or network programming including TCP/UDP and multicast market data.
- Preferred: Python proficiency for rapid prototyping, data analysis, and integration with C++ modules.
- Preferred: open-source contributions.
Benefits
- Three- to six-month internship including the summer.
- One-on-one mentorship from senior quantitative engineers and researchers.
- Dedicated manager and mentor throughout the internship.
- Exposure to production-grade trading systems and modern AI tooling.
- Learning sessions, hands-on skills workshops, networking events, and educational opportunities.
- Potential path to a full-time role.
About Schonfeld
Schonfeld is a privately held, multi-manager hedge fund that allocates capital to internal and external portfolio managers across quantitative, fundamental equity, tactical trading, and discretionary macro/fixed-income strategies. The firm manages money for institutional and other sophisticated investors and supports teams with proprietary technology, infrastructure, and risk analytics. Founded in 1988 and headquartered in New York, it operates globally with an investing footprint spanning five continents.