Jobs at Quadeye

Develop and optimize quantitative trading strategies for derivatives and crypto markets. Responsibilities include researching predictive signals, applying statistical and machine learning techniques, backtesting strategies, writing production-quality code, deploying and monitoring live strategies, investigating anomalies, and improving performance across the full research-to-production lifecycle.

Develop and optimize quantitative trading strategies using large-scale financial datasets, statistical modeling, machine learning, and data analysis. Responsibilities span signal development, backtesting, production implementation, performance monitoring, and optimization. The role requires writing scalable code for live trading systems, diagnosing strategy behavior, collaborating with researchers, traders, and engineers, and continuously improving prediction and execution performance.

Monitor and maintain production high-frequency trading systems, investigate alerts and incidents, troubleshoot operational issues, support deployments, and improve reliability. Develop Python and Shell/Bash automation tools, maintain monitoring dashboards, optimize workflows, and collaborate with developers and traders to resolve production bottlenecks in a time-sensitive environment.

Conduct quantitative research on financial markets, analyze large datasets, develop trading signals and models, design backtests, and help implement research ideas in live trading systems. The role involves mathematical and statistical analysis, programming, market microstructure research, strategy evaluation, and collaboration with quantitative researchers and engineers.

Research and develop data-driven trading strategies for global financial markets using statistical and machine learning techniques. Responsibilities include analyzing large datasets, writing optimized production code, deploying and monitoring strategies, investigating anomalies, and refining predictive models. The role requires strong quantitative aptitude, algorithms and object-oriented programming knowledge, Linux proficiency, and the ability to work effectively in a fast-paced environment.

Develop and maintain trading infrastructure, including pre-trading pipelines, post-trading reports, latency monitoring, alpha analytics, dashboards, predictors, and workflow automation. Support trading platform deployments, troubleshoot production issues, analyze simulation versus production performance, and improve system reliability. Collaborate with traders, researchers, and engineers in a fast-paced, low-latency environment.

Interns will design, implement, optimize, test, deploy, and monitor ultra-low-latency trading and risk-management systems. Responsibilities include real-time system development, CPU and cache optimization, OS-level tuning, high-performance networking, kernel and microarchitecture research, lock-free data structures, and performance-monitoring tool development. Interns collaborate with quantitative researchers, traders, and infrastructure engineers while gaining experience with production systems and potential full-time conversion.

As a Full Stack Engineering Intern, you will build and enhance internal web applications for trading, quant, infrastructure, compliance, and operations teams. Responsibilities include developing data manipulation and trade monitoring tools, improving system reliability and user experience, proposing and justifying solutions, and owning development, testing, deployment, and monitoring. The role requires collaboration in a fast-paced environment and exposure to scalable, real-time systems.

Monitor and support live high-frequency trading systems across global electronic markets. Responsibilities include managing startup and shutdown procedures, responding to market alerts and outages, coordinating with exchanges and trading teams, and using scripting and data manipulation in a fast-paced environment. The role requires rotational shifts, strong communication, Unix experience, monitoring-tool knowledge, and the ability to manage high-priority issues under pressure.

Quantitative Strategist Interns conduct mathematical, statistical, and programming research to develop and backtest trading strategies. They analyze market data, microstructure, and strategy performance; improve research methodologies; build quantitative models and tools; and develop features for live, low-latency trading systems. The role is designed for engineering students with strong quantitative, analytical, algorithmic, and object-oriented programming skills.

Manage and administer Linux hardware, software, storage, firewall, and trading infrastructure in a 24/7 production environment. Provide hands-on support for colocated, office, and data center systems; troubleshoot servers, hardware, installations, and upgrades; monitor infrastructure; optimize systems for low latency; and support high-priority production issues and projects.