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- Tasks: Optimise large-scale workloads on GPU and CPU for enhanced performance.
- Company: Leading financial services firm based in London.
- Benefits: Competitive salary, 35 days annual leave, and excellent perks.
- Why this job: Join a dynamic team and make a real impact in financial technology.
- Qualifications: Degree in computer science and expertise in Python, C++, and deep learning frameworks.
- Other info: Hands-on role with opportunities for professional growth.
The predicted salary is between 43200 - 72000 £ per year.
A leading financial services firm based in London is seeking a talented ML Performance Engineer. In this hands-on role, you will optimize large-scale workloads across GPU and CPU infrastructure to enhance performance and efficiency of research workloads.
The ideal candidate should possess a degree in computer science and have strong expertise in Python, C++, and various deep learning frameworks, among other skills.
Excellent compensation and benefits are offered, including a competitive salary, 35 days of annual leave, and more.
ML Performance Engineer: Optimize Large-Scale GPU/CPU in London employer: G-Research
Contact Detail:
G-Research Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Performance Engineer: Optimize Large-Scale GPU/CPU in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the financial services sector, especially those working with ML and performance engineering. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to GPU/CPU optimisation and deep learning frameworks. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and C++ skills. Practice coding challenges and be ready to discuss your past experiences with optimising workloads. Confidence is key, so let’s nail those interviews together!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace ML Performance Engineer: Optimize Large-Scale GPU/CPU in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, C++, and deep learning frameworks. We want to see how your skills align with the role of an ML Performance Engineer, so don’t hold back on 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 optimising workloads and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any large-scale GPU/CPU projects, make sure to mention them! We’re interested in real-world applications of your skills, so include links or descriptions of your work that demonstrate your expertise.
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’s super easy – just follow the prompts and you’ll be set!
How to prepare for a job interview at G-Research
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of Python, C++, and deep learning frameworks. Be ready to discuss specific projects where you've optimised workloads or improved performance. This will show that you not only understand the theory but can apply it practically.
✨Showcase Your Problem-Solving Skills
Prepare to tackle some technical challenges during the interview. Think about how you would approach optimising a large-scale workload. Practise explaining your thought process clearly, as this will demonstrate your analytical skills and ability to think on your feet.
✨Research the Company Culture
Get familiar with the financial services firm’s values and work environment. Tailor your responses to reflect how your personal values align with theirs. This will help you connect with the interviewers and show that you're genuinely interested in being part of their team.
✨Ask Insightful Questions
Prepare a few thoughtful questions about the role and the company. Inquire about their current projects or challenges they face with GPU/CPU optimisation. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
