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- Tasks: Lead a team to optimise large-scale workloads in cutting-edge compute environments.
- Company: Join a leading firm in quantitative finance with a focus on innovation.
- Benefits: Competitive salary, 35 days leave, healthcare, and monthly events.
- Why this job: Shape the future of performance engineering and make a real impact.
- Qualifications: Experience in managing engineers and optimising large-scale workloads.
- Other info: Enjoy a flexible work environment with excellent career growth opportunities.
The predicted salary is between 48000 - 84000 £ per year.
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.
We are seeking an exceptional Engineering Manager to lead our Compute Performance Engineering team. The team’s mission is to optimise large-scale workloads across our Linux HPC and Kubernetes compute environments. This is a hands‑on, impactful role where you will design and implement techniques to maximise utilisation of our cutting‑edge compute infrastructure — ensuring researchers and engineers achieve the best possible performance on current and future systems. You will work closely with internal research and infrastructure teams to profile and analyse workloads, eliminate bottlenecks and develop reference solutions. Your work will directly influence the evolution of our platforms — shaping the architecture, software stack and tooling that underpin large‑scale machine learning computation.
Key responsibilities of the role include:
- Defining and delivering the long‑term strategy for performance engineering across G-Research, enabling all engineers to maximise utilisation of our compute estate
- Providing leadership, mentoring and career development for engineers, fostering a high-performance culture
- Communicating performance improvements and team impact effectively across technical and non-technical audiences
- Engaging directly with researchers, senior stakeholders and engineers to understand compute challenges and design optimised solutions
- Profiling, benchmarking and tuning large‑scale workloads across CPU, GPU and memory-intensive jobs
- Developing reference implementations, libraries and tools to improve job efficiency and reliability
- Collaborating with systems, architecture and platform teams to evolve our compute stack
- Influencing long-term platform and infrastructure decisions
Who are we looking for?
We need a technically credible leader with a passion for performance at scale. You’ll bring a combination of deep systems knowledge with the ability to lead and grow a high-performing team. The ideal candidate will have the following skills and experience:
- Experience managing and developing engineers
- A strong background in computer science, such as BSc, MSc, PhD or equivalent experience
- Proven expertise in profiling, benchmarking and optimising distributed or large-scale workloads
- Proficiency in one or more programming languages, with strong grounding in algorithms and performance optimisation
- Deep understanding of Linux internals, for example across scheduling, memory management, NUMA, networking and filesystems
- Experience with HPC schedulers and Kubernetes workload orchestration
- Hands‑on experience with heterogeneous compute, such as GPUs, multi-core CPU workloads and high-memory systems
- Excellent communication and collaboration skills across research, infrastructure and engineering domains
- Familiarity with profiling and monitoring tools, including perf, eBPF, VTune, Flamegraphs, Prometheus and Grafana
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
Performance Engineering Manager in London employer: G-Research
Contact Detail:
G-Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Performance Engineering Manager in London
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. Getting to know the team can give you insider info and make your application stand out.
✨Tip Number 2
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your past projects. We want to see how you tackle complex problems, so have some examples up your sleeve.
✨Tip Number 3
Show your passion for performance engineering! Talk about your experiences with HPC, Kubernetes, and any cool projects you've worked on. Let us know why you're excited about optimising compute environments.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining our team.
We think you need these skills to ace Performance Engineering Manager in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your background in performance engineering and any relevant projects you've worked on. We want to see how you can bring scientific clarity to financial complexity!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about performance at scale and how your leadership style can foster a high-performance culture. Remember, we value methodical execution, so be clear and concise.
Showcase Your Technical Skills: Don’t shy away from listing your technical expertise! Mention your experience with profiling tools, HPC schedulers, and any programming languages you’re proficient in. We’re looking for someone who can optimise large-scale workloads, so make it clear how you fit the bill.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at G-Research
✨Know Your Tech Inside Out
Make sure you brush up on your technical knowledge, especially around Linux internals and performance optimisation. Be ready to discuss specific examples of how you've profiled and optimised workloads in the past. This will show that you not only understand the theory but can apply it practically.
✨Showcase Your Leadership Skills
Prepare to talk about your experience managing and developing engineers. Think of specific instances where you've fostered a high-performance culture or mentored team members. This is crucial as the role requires strong leadership capabilities.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You’ll need to communicate effectively with both technical and non-technical audiences, so being able to break down your ideas will be key to demonstrating your fit for the role.
✨Engage with Real Scenarios
Be ready to discuss real-world compute challenges you've faced and how you approached solving them. Think about how you collaborated with other teams to design optimised solutions, as this will highlight your collaborative spirit and problem-solving skills.
