At a Glance
- Tasks: Optimise large-scale GPU/CPU workloads for cutting-edge research projects.
- Company: Barlowe LLP, a forward-thinking tech firm in Greater London.
- Benefits: Highly competitive salary, extensive benefits, and great work/life balance.
- Other info: Collaborative environment with opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact in machine learning performance.
- Qualifications: Degree in computer science or equivalent, with skills in Python, C++, and deep learning.
The predicted salary is between 60000 - 80000 £ per year.
Barlowe LLP in Greater London is seeking an exceptional ML Performance Engineer to optimise large-scale workloads across GPU and CPU infrastructure. In this hands-on role, you will design techniques to improve performance for research workloads while collaborating with cross-functional teams.
The ideal candidate holds a degree in computer science or equivalent, with strong experience in Python, C++, and deep learning frameworks.
The position offers a highly competitive compensation, extensive benefits, and an excellent work/life balance.
ML Performance Engineer: Scale GPU/CPU Workloads for Research in London employer: Barlowe LLP
Barlowe LLP is an outstanding employer located in Greater London, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from a highly competitive compensation package, extensive benefits, and a strong emphasis on work/life balance, alongside ample opportunities for professional growth and development in the rapidly evolving field of machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land ML Performance Engineer: Scale GPU/CPU Workloads for Research in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We can’t stress enough how important it is to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, C++, and deep learning frameworks. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions related to ML performance engineering. We recommend practising with friends or using online resources to get comfortable with the types of questions you might face.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace ML Performance Engineer: Scale GPU/CPU Workloads for Research 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 at Barlowe LLP. Keep it engaging and personal!
Showcase Your Problem-Solving Skills:In your application, highlight specific examples where you've tackled performance issues or optimised processes. We love seeing how you approach challenges, especially in a hands-on role like this one!
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 don’t miss out on any important updates. Plus, we can’t wait to hear from you!
How to prepare for a job interview at Barlowe LLP
✨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 also have practical experience.
✨Showcase Your Problem-Solving Skills
Prepare to tackle hypothetical scenarios related to GPU and CPU workload optimisation. Think about how you would approach common challenges in ML performance engineering. This will demonstrate your analytical thinking and ability to collaborate with cross-functional teams.
✨Research Barlowe LLP
Familiarise yourself with Barlowe LLP’s work and values. Understanding their projects and culture can help you tailor your responses and show genuine interest in the role. Plus, it gives you a chance to ask insightful questions during the interview.
✨Practice Your Communication Skills
Since this role involves collaboration, practice explaining complex technical concepts in simple terms. Being able to communicate effectively with non-technical team members is crucial, so think of examples where you've done this successfully.
