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Quantitative Developer

External
Full-timeRemoteToday
PythonJava
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About the role

Position Overview We are looking for a Quantitative Developer to build and optimize high-performance trading systems with a focus on trade execution, order management systems (OMS), and low-latency infrastructure. You will work closely with traders, quants, and infrastructure teams to design systems that directly impact trading performance and PnL. Key Responsibilities ● Design and develop low-latency trade execution systems and order management systems (OMS) ● Build and optimize high-frequency trading (HFT) infrastructure for performance and scalability ● Develop exchange connectivity, execution gateways, and market access components ● Improve network performance and latency through kernel/network stack optimizations ● Build and maintain real-time data pipelines for market data ingestion and processing ● Work on multithreaded and distributed systems for high-throughput environments ● Collaborate with quant researchers and traders to translate strategies into production systems ● Perform performance profiling, benchmarking, and system tuning ● Ensure system reliability, fault tolerance, and monitoring in live trading environments Requirements ● 3-5 years of experience in quantitative development / low-latency systems / trading infrastructure ● Strong programming skills in C++ (preferred) or Java/Python (performance-critical systems exposure required) ● Hands-on experience with Trade execution systems / OMS, HFT or low-latency trading systems, exchange connectivity (FIX, binary protocols, market data feeds) ● Solid understanding of multithreading, concurrency, and memory optimization, linux systems programming, network programming (TCP/UDP, sockets, kernel bypass - DPDK/Solarflare is a plus) ● Experience in network optimization and latency reduction techniques Quantitative Developer ● Exposure to real-time data pipelines / streaming systems ● Strong problem-solving and debugging skills in performance-critical environments ● Work on cutting-edge low-latency trading systems ● Direct impact on trading performance and revenue generation ● High learning curve with exposure to quant research + execution stack ● Competitive compensation with performance-linked upside


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