My client is a crypto market-making firm. This role is fully remote.
Role Overview The Quantitative R&D Engineer works closely with quantitative traders and research teams to design, develop, and continuously optimize high-frequency trading systems and supporting infrastructure. This role focuses on building low-latency, high-throughput, and highly reliable trading platforms, enabling strategies to move seamlessly from research and backtesting into live trading, while continuously improving execution efficiency and system robustness.

Responsibilities Design, develop, and optimize high-frequency / quantitative trading systems, including execution, market data processing, risk control, and monitoring modules Build and maintain low-latency, high-throughput trading infrastructure, continuously improving end-to-end execution performance Support quantitative traders in strategy deployment, backtesting, simulation, and live trading validation Collaborate with trading teams to integrate exchanges, market makers, and liquidity venues, and optimize execution performance Provide system-level feasibility analysis and technical evaluation during early-stage strategy research Drive the smooth transition of strategies from research environments to stable, scalable production systems Design and implement real-time monitoring and key performance metrics, including latency, throughput, slippage, and fill rate Own system stability, fault tolerance, capacity planning, and disaster recovery mechanisms Continuously improve system reliability and performance under extreme market conditions
Qualifications Bachelor’s degree or above in Computer Science, Software Engineering, Mathematics, Physics, or a related field Strong proficiency in at least one systems-level programming language (C++ / Rust / Python), with 3+ years of experience in quantitative or trading system development Deep understanding of low-latency system design, including networking, memory management, concurrency models, and performance optimization Solid experience with Linux / UNIX systems and internals (processes, threads, scheduling, network stack) Hands-on experience with high-performance data processing, including market data, time-series data, and real-time streaming pipelines Familiarity with relational databases, time-series databases, and in-memory data stores Strong knowledge of multithreading, asynchronous I/O, locking mechanisms, and lock-free data structures Practical experience with trading APIs and protocols such as FIX, Web Socket, and REST Ability to independently design, build, test, and troubleshoot trading connectivity, order execution, risk control, and exception handling workflows Experience with cloud-native architectures (AWS) or bare-metal, low-latency deployments Excellent problem-solving and system debugging skills, with the ability to operate effectively under high-pressure environments Fluent in English; Mandarin is a plus
Nice to Have Experience building HFT, market-making, or arbitrage trading systems Strong understanding of matching engines, order book structures, and market microstructure Hands-on experience with FPGA, DPDK, RDMA, or kernel-bypass networking technologies Familiarity with crypto / digital asset exchange high-frequency trading architectures Experience operating and maintaining production trading systems during extreme or highly volatile market conditions