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- Tasks: Lead a team to optimise performance in Linux HPC and Kubernetes environments.
- Company: Top-tier quantitative finance firm with a focus on innovation.
- Benefits: Competitive salary, annual bonus, and great work-life balance.
- Why this job: Join a dynamic team and make a significant impact in performance engineering.
- Qualifications: Strong computer science background and experience in managing engineering teams.
The predicted salary is between 43200 - 72000 £ per year.
A leading quantitative finance firm is seeking an exceptional Engineering Manager to lead their Compute Performance Engineering team in London. The successful candidate will design and implement strategies to maximise performance across Linux HPC and Kubernetes environments.
With a strong background in computer science, candidates should have experience managing engineers and optimising large-scale workloads.
This role offers a competitive salary, annual discretionary bonus, and excellent work-life balance.
Performance Engineering Manager - HPC & Kubernetes 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 - HPC & Kubernetes in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio or any projects that highlight your experience with HPC and Kubernetes, make sure to share them during interviews. It’s all about demonstrating what you can bring to the table.
✨Tip Number 3
Prepare for those tricky questions! Brush up on common performance engineering scenarios and be ready to discuss how you’d tackle them. We want to see your problem-solving skills in action!
✨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, we love seeing candidates who take that extra step!
We think you need these skills to ace Performance Engineering Manager - HPC & Kubernetes in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in managing engineers and optimising workloads, especially in Linux HPC and Kubernetes. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about performance engineering and how your skills can benefit our Compute Performance Engineering team. Let us know what excites you about this opportunity!
Showcase Your Leadership Skills: As an Engineering Manager, your leadership experience is key. In your application, share examples of how you've successfully managed teams and driven performance improvements. We love to see how you inspire and motivate others!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you get the best possible experience. Plus, we can’t wait to see your application!
How to prepare for a job interview at G-Research
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of Linux HPC and Kubernetes. Be ready to discuss specific strategies you've implemented in the past to optimise performance, as well as any challenges you've faced and how you overcame them.
✨Showcase Your Leadership Skills
As a Performance Engineering Manager, you'll need to demonstrate your ability to manage and inspire a team. Prepare examples of how you've successfully led engineers in previous roles, focusing on your approach to mentoring and fostering collaboration.
✨Prepare for Technical Questions
Expect in-depth technical questions related to performance engineering. Brush up on concepts like workload optimisation and resource management. Practising with mock interviews can help you articulate your thought process clearly.
✨Highlight Your Problem-Solving Abilities
Be ready to discuss specific instances where you've tackled complex performance issues. Use the STAR method (Situation, Task, Action, Result) to structure your answers, showcasing your analytical skills and how you drive results.
