We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.
From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve. Together we’re building a world-class platform to amplify our teams’ most powerful ideas.
As part of our engineering team, you’ll shape the platforms and tools that drive high-impact research - designing systems that scale, accelerate discovery and support innovation across the firm.
Take the next step in your career.
The role
We are seeking an exceptional Computer Performance Engineer to optimise large-scale workloads across our Linux HPC and Kubernetes compute environments.
This is a hands-on, impactful role. You will design and implement techniques that maximise utilisation of cutting-edge compute infrastructure, ensuring our researchers and engineers achieve the best possible performance on current and future systems.
You will work directly with internal research teams and infrastructure engineers to profile and analyse workloads, eliminate bottlenecks and develop reference solutions. Your work will influence long-term platform evolution and help shape the architecture, software stack and tooling that underpins large-scale machine learning computation.
Key responsibilities of the role include:
Collaborating with researchers, senior stakeholders and engineers to understand their compute challenges and design optimised solutions
Profiling, benchmarking and tuning large-scale workloads for performance across CPU, GPU and memory-intensive jobs
Developing reference implementations, libraries and tools to improve job efficiency and reliability
Collaborating closely with systems, architecture and platform teams to evolve our compute stack
Influencing long-term platform and infrastructure decisions
Who are we looking for?
The ideal candidate will have the following skills and experience:
Bachelors, Masters or PhD degree in computer science, or equivalent experience
Proven track record of profiling, benchmarking and optimising distributed or cloud-scale workloads
Strong knowledge of one or more programming languages, with solid grounding in algorithms and performance engineering
Deep understanding of Linux internals, such as scheduling, memory management, NUMA, networking and filesystems
Experience with HPC schedulers and Kubernetes workload orchestration
Familiarity with profiling and monitoring tools, such as perf, eBPF, VTune, Flamegraphs, Prometheus and Grafana
Hands-on experience with heterogeneous compute, including GPUs, multi-core CPU workloads and high-memory systems
Strong communication skills with the ability to collaborate across research, infrastructure and engineering teams
Why should you apply?
- Highly competitive compensation plus annual discretionary bonus
- Lunch provided (via Just Eat for Business) and dedicated barista bar
- 35 days’ annual leave
- 9% company pension contributions
- Informal dress code and excellent work/life balance
- Comprehensive healthcare and life assurance
- Cycle-to-work scheme
- Monthly company events
