Note: The job is a remote job and is open to candidates in USA. DeepFin Research is a proprietary high-frequency trading firm that combines deep learning and traditional quantitative research methods to trade global markets. They are seeking exceptional HFT software engineers to build their trading infrastructure, working on various components from connectivity to execution in a high-performance environment.

Responsibilities

• Design, implement, and optimize ultra-low-latency, zero-allocation trading engines in modern C++
• Develop and maintain market data handlers and execution gateways utilizing protocols like FIX, OUCH, ITCH, and raw UDP multicast
• Optimize system critical paths through OS-level tuning, CPU pinning, cache-line optimization, and NUMA-aware programming
• Interface with hardware-accelerated components, working alongside FPGA engineers to integrate PCIe/DMA data pipelines
• Implement kernel-bypass networking solutions (e.g., Solarflare OpenOnload, DPDK) to minimize network stack latency
• Collaborate directly with AI researchers and quantitative traders to deploy complex quantitative models into strict, latency-sensitive production environments
• Work end-to-end on projects from the ground up – this is not a role to focus on specialised parts of the infrastructure stack, but rather to see projects through end-to-end

Skills

• 1–3 years of experience in low-latency software engineering for Junior candidates; 3–10+ years for Senior candidates
• Exceptional expertise in C++ with a deep understanding of lock-free data structures, custom memory allocators, and hardware architecture
• Proven experience building systems in HFT or highly concurrent, real-time computing environments
• Strong grasp of Linux internals, network programming (TCP/IP, UDP), and performance profiling tools (e.g., perf, VTune)
• Solid understanding of futures markets microstructure; exposure to FX and options markets is a strong plus
• Entrepreneurial mindset with the communication skills required to thrive in a fast-paced, highly collaborative environment, preferring end-to-end ownership over extreme specialization

Company Overview