My clients is seeking an experienced Quantitative Developer to design, build, and optimise high-performance trading systems within prediction markets and market-making environments. This role is suited to candidates with a proven track record delivering high Sharpe strategies in HFT or similarly latency-sensitive domains.
You will work on end-to-end system development, including signal research, execution infrastructure, and real-time risk management. The ideal candidate combines strong engineering discipline with a deep understanding of market microstructure, probabilistic modelling, and alpha generation.
Key Responsibilities:
* Develop and maintain low-latency trading systems in Java, Python, or Rust
* Design and implement predictive models for pricing and execution
* Optimise market-making strategies across multiple venues
* Build robust backtesting and simulation frameworks
* Collaborate closely with researchers and traders to deploy live strategies
* Continuously improve system performance, reliability, and scalability
Requirements:
* Extensive experience in HFT, market making, or prediction markets
* Demonstrated ability to generate high Sharpe ratio strategies
* Strong programming skills in Java, Python, or Rust
* Deep knowledge of data structures, algorithms, and concurrency
* Solid understanding of market microstructure and execution dynamics
* Experience working with large datasets and real-time data pipelines
* Degree in a quantitative field (Maths, Physics, Computer Science, Engineering)
Desirable:
* Experience with exchange connectivity, FIX protocols, or crypto markets
* Background in statistical modelling, ML, or probabilistic forecasting
* Familiarity with Linux systems, networking, and performance tuning
Location & Flexibility:
* Preferably London-based, but open to remote candidates within compatible time zones
This is a high-impact role in a fast-moving environment, offering significant autonomy and the opportunity to directly influence trading performance.