Quadeye is a leading algorithmic trading firm with its presence across all global exchanges specializing in cutting-edge quantitative strategies and market making. Our team is dedicated to driving innovation in financial markets through advanced statistical models, data science, and algorithmic execution. We pride ourselves on fostering a collaborative environment where technical expertise and creative problem-solving are at the forefront of our trading strategies.
We are seeking an exceptional Quantitative Developer to join our dynamic research team. The ideal candidate will have a strong background in optimizing quantitative models and research code, with expertise in high-performance computing, CPU/GPU communication, and system architecture. This role will involve working closely with quantitative researchers to translate their models into production-ready, high-performance systems.
Job Location : Romania
Your responsibilities will include:
- Performance Optimization: Identify and implement optimizations for quantitative research code, including statistical models, alpha signals, and feature generation, to achieve significant runtime improvements.
- Low-Latency Implementation: Develop and refine low-latency implementations of trading strategies and analytical tools, ensuring high throughput and minimal delay in live trading environments.
- CPU/GPU Optimization: Design and implement efficient CPU/GPU communication strategies and leverage parallel computing techniques to accelerate complex quantitative computations.
- Production Infrastructure: Collaborate with engineering teams to build and maintain robust, scalable, and performant infrastructure for deploying and managing quantitative models in production.
- Debugging and Troubleshooting: Diagnose and resolve performance bottlenecks, system issues, and inefficiencies in existing quantitative systems.
- Code Quality and Best Practices: Establish and enforce coding standards, best practices, and rigorous testing methodologies to ensure the reliability and maintainability of quantitative codebases.
- Collaboration: Work closely with quantitative researchers, traders, and other engineers to understand system requirements, provide technical guidance, and contribute to the overall architectural design of trading systems.
An ideal candidate should have:
- Strong experience in software development, particularly in optimizing quantitative models and research code for high-frequency or algorithmic trading.
- Extensive experience with high-performance computing, parallel programming, and optimizing CPU/GPU interactions.
- Proficiency in programming (C++, Python, or similar) with a deep understanding of data structures, algorithms, and system-level programming.
- Experience with tools and libraries for numerical computation and performance profiling.
- Education: A degree in a quantitative field such as Computer Science, AI/ML or similar.
Skills :
- Excellent problem-solving abilities with a strong analytical and technical foundation.
- Experience with time-series data and financial market data.
- Ability to analyze and optimize code for performance, memory usage, and concurrency.
- Strong communication skills and the ability to collaborate with cross-functional teams, including researchers and traders.
Preferred Skills :
- Experience in high-frequency trading or market-making environments.
- Familiarity with low-latency programming techniques and network protocols.
- A proven track record of delivering performance improvements in live trading systems.
Top Skills
What We Do
Quadeye combines the best of both worlds: the opportunity and spirit of a startup and the stability of an established, experienced firm. Our employees work hard to solve interesting problems, and their results are rewarded. We value continuous learning—from our outcomes, from the environment and from each other.
By having deepest possible understanding of the financial markets and translating that understanding into great automated trading strategies, we have built a distinct track record of success. We trade across many asset classes and instruments, using a variety of models, across the globe.
