I am looking to partner with a seasoned quantitative developer who truly understands how professional desks operate and can help push my existing intraday and high-frequency trading stack to the next level. The infrastructure already handles 3,000-35,000 fills per symbol each day; what I need now is sharper algorithmic strategies that squeeze more edge out of real-time market data feeds while keeping latency and slippage to a minimum. You will dig straight into our live production codebase, analyse current performance, design new logic, and fine-tune execution paths. Depth-of-book updates, order book imbalance, micro-structure patterns, and exchange-specific quirks are all fair game if they improve P&L. I am ready to share historical tick archives, replay tools, and direct feed connectivity so you can research, back-test, and iterate rapidly. Key deliverables: • New or refined strategy modules with fully reproducible back-tests • Benchmarks that demonstrate uplift in hit-rate, risk-adjusted returns, and capacity under realistic fill assumptions • Production-ready code (Python/C++ preferred, but open to other low-latency choices) with clean hooks into existing risk and execution layers • Concise documentation outlining logic, parameters, and deployment steps Experience with exchange colocation, event-driven architectures, GPU acceleration, or advanced statistical modelling will stand out, but what matters most is the ability to translate quantitative insight into real, scalable profit. If that sounds like you, let’s talk and start shipping improvements right away.