About Quadeye Quadeye is an algorithmic trading firm operating across major global financial markets and exchanges. We combine quantitative research, advanced mathematical modeling, and high-performance technology to develop sophisticated automated trading strategies across diverse asset classes. Our teams work at the intersection of markets, mathematics, statistics, and technology, with significant ownership across the entire strategy lifecycle—from research and ideation to implementation, deployment, and optimization. We offer a highly meritocratic environment where talented researchers and engineers have the opportunity to work on challenging problems, access world-class infrastructure, and see the direct impact of their work on live trading performance. The Role We are looking for a Systems Engineer to design, develop, and optimize robust, resilient, and high-performance trading systems that directly power Quadeye’s proprietary trading strategies. You will work on real-time trade execution and risk management systems while solving complex engineering challenges across low-latency and high-performance computing environments. This is a high-ownership role where you will work closely with engineers, quantitative researchers, and traders and contribute across the full development lifecycle—from system design and implementation to testing, deployment, monitoring, and performance optimization. What You’ll Do • Design and implement real-time trade execution and risk management systems with nanosecond-level latency sensitivity. • Develop robust, reliable, and scalable systems for production trading environments. • Identify performance bottlenecks and optimize code to achieve lower latency and higher throughput. • Take end-to-end ownership of modules, including requirements gathering, design, implementation, testing, and deployment. • Research and experiment with techniques to reduce latency across the operating system, kernel, and networking stack. • Explore kernel bypass, system tuning, CPU architecture, and cache-efficient data structures to improve system performance. • Design and implement scalable algorithms for latency-sensitive trading applications. • Develop and deploy performance monitoring tools for CPU, network, and memory utilization. • Analyze system performance and identify opportunities to improve latency, throughput, reliability, and resource utilization. • Troubleshoot performance and reliability issues in production-critical systems. • Continuously improve the efficiency, robustness, and scalability of trading infrastructure. • Collaborate closely with engineers, quantitative researchers, and traders to deliver high-performance and highly reliable trading systems. Requirements • Engineering degree in Computer Science or an equivalent discipline from a premier institution. • Strong problem-solving skills and quantitative aptitude. • Solid understanding of data structures, algorithms, and object-oriented programming. • Experience with C++ or C is preferred. • Working knowledge of Linux systems. • Ability to multitask and perform effectively in a fast-paced environment. • Strong work ethic and communication skills. • Knowledge of Python or Perl is a plus.