Quantitative Developer | Global Electronic Trading Firm | London Engineering at the Frontier of Electronic Markets

Quantitative Developer | Global Electronic Trading Firm | London Engineering at the Frontier of Electronic Markets

The Role

You will work on the production systems that make markets globally. This is a quantitative engineering role operating at the intersection of:

• Ultra-low-latency systems engineering,
• Real-time pricing and risk
• Market microstructure and execution
• Distributed systems at extreme throughput
• Machine learning inference in hard latency budgets

The engineering problems here are not theoretical. Every microsecond of latency has a measurable impact on fill quality and market share. Every system failure has a direct P&L consequence. The expectations on code quality, system design, and operational discipline are correspondingly serious.

What You Could Be Working On

Low-Latency Execution Infrastructure Building and optimising the execution path from signal to resting order on exchange.

This means:

• Kernel bypass networking: DPDK, RDMA, custom NIC drivers
• FPGA-accelerated order routing and market data processing
• Co-location infrastructure across major global venues
• CPU affinity, IRQ pinning, and memory layout optimisation
• Nanosecond-resolution profiling and latency measurement
• Exchange connectivity — FIX, native binary protocols, drop copy

Latency budgets are real and enforced. The engineers working here understand the full path from wire to application and back.

Real-Time Pricing and Risk Systems

Building the systems that generate, update, and hedge quotes across millions of instruments simultaneously.

This includes:

• High-throughput market data normalisation and distribution
• Real-time options pricing engines — Black-Scholes, local vol, stochastic vol models
• Greeks computation and dynamic hedge execution
• Portfolio-level risk aggregation with sub-millisecond refresh rates
• Position and exposure management under continuous market movement

ML Inference in Production

Deploying machine learning models into live trading systems where latency and determinism are hard constraints.

The challenge is not model development — it is operating ML at the execution layer:

• Serving inference within microsecond or low-millisecond budgets
• GPU and CPU inference pipeline optimisation
• Feature computation from live order book and trade data
• Model versioning and live rollover without trading interruption
• Feedback loops for real-time model performance monitoring

Why Engineers Join

The attraction is the technical environment itself.

• Problems that exist at no other employer; the scale, latency requirements, and market exposure are unique at the systems level,
• Direct exposure to production consequences; your work runs in live markets from day one
• Intellectual peers drawn from the top of systems engineering, mathematics, and physics globally
• Engineering is not a support function; it is the core competency of the business

Strong engineers are given ownership of critical systems quickly. You'll need to understand your system end to end and be accountable for it in production.

If you are an engineer who wants to work at the frontier of what is technically possible in production systems at a firm that is definitely operating at a global scale. This is one of a very small number of roles in the market that deliver on that.