FPGA Engineer - Low Latency Trading
Engineering · London · Full-time · On-site
Annual base salary: £190,000 – £195,000 GBP
Role description
Westren Capital is a research-driven quantitative investment firm focused on systematic strategies across global markets. We hire from Mathematics, Physics, Computer Science and related fields, not for credentials, but for the ability to reason clearly under uncertainty and build things that work in production.
Our work sits at the intersection of statistical modelling, market microstructure, and engineering. The aim is straightforward, if not easy: extract durable signals from noisy data and convert them into scalable, risk-aware strategies. That requires intellectual honesty, a tolerance for ambiguity, and a willingness to discard ideas that do not survive contact with reality.
We operate in small, highly collaborative teams where research, engineering, and trading are tightly coupled. Outcomes matter. Not narratives, not backtests that look good in isolation, but strategies that hold up live. Compensation and progression reflect that directly.
Beyond trading, we invest in building internal tools, data infrastructure, and research workflows that compound over time. The edge is rarely a single idea; it is the system that produces and evolves ideas faster than others.
Responsibilities:
Throughout the recruitment process, we don’t shuffle you into teams like pieces on a board. We map your edge. Skills, instincts, tolerance for pressure. Then place you where that edge compounds.
The FPGA team at Westren builds the layer where time actually matters. Not in theory, not in backtests, but in nanoseconds that decide whether you trade or watch someone else take it. We design ultra-low-latency hardware systems that sit directly in the critical path of our trading stack. Custom logic on cutting-edge FPGA devices, tuned until there’s nothing left to remove.
This is not “hardware vs software.” It’s both, collapsed into one surface. SystemVerilog where cycles are carved out, C++ and Python where control, testing, and orchestration live. The outcome is simple: market data in, decisions out, faster than the rest of the street.
As an intern or graduate in the FPGA team, you will:
Work on live trading systems. Not toy problems. Code that ships, signals that route, decisions that execute.
Design and optimise FPGA pipelines where latency is measured, hunted, and reduced relentlessly.
Use SystemVerilog, C++, and Python to build and validate high-performance systems under real market conditions.
Implement and verify features that directly improve market data handling and order execution speed.
Collaborate tightly with quants and software engineers, because speed without strategy is just noise.
Debug, profile, and refine systems where inefficiency is not tolerated, only removed.
Work with state-of-the-art FPGA hardware and toolchains used in modern HFT environments.
Contribute to ongoing R&D as we push closer to physical limits of execution.
Requirements
Requirements:
Penultimate or final-year student pursuing a Bachelor’s, Master’s, or PhD in Engineering, Computer Science, Electrical Engineering, or a related field, on track for a 2:1 or above from a leading institution. We don’t fetishise grades, but they tend to signal you can handle non-trivial systems without falling apart.
Demonstrated interest in technology through real work. Software builds, hardware tinkering, side projects that went wrong before they went right. Formal Computer Science training is optional. Evidence of curiosity is not.
Exposure to HDL such as SystemVerilog, Verilog, or VHDL, with a working sense of how designs translate into actual hardware behaviour.
Programming ability in C++ and/or Python that goes beyond syntax. You should be able to build, test, and iterate without hand-holding.
Understanding of digital logic design, computer architecture, and the practical challenges of high-speed data movement. At some point, theory has to meet timing constraints.
Familiarity with FPGA toolchains like Xilinx Vivado or Intel Quartus is useful. If you haven’t used them, you’ll be expected to get productive quickly.
Strong analytical and problem-solving ability. You debug methodically, optimise deliberately, and treat latency, resource usage, and power as real constraints, not academic concepts.
Proactive and curious mindset. You ask questions early, challenge assumptions when needed, and close knowledge gaps without waiting to be told.
Entrepreneurial, self-motivated, and results-driven. You take ownership, push work forward, and care about whether the system performs, not whether the process looked neat on paper.