At a Glance
- Tasks: Optimise ML inference on edge devices and tackle performance bottlenecks.
- Company: Wayve, a forward-thinking tech company based in London.
- Benefits: Hybrid working model for flexibility, competitive salary, and growth opportunities.
- Other info: Dynamic work environment with a focus on innovation and collaboration.
- Why this job: Join a cutting-edge team and make a real impact in AI technology.
- Qualifications: Experience with production systems and tools like TensorRT and CUDA.
The predicted salary is between 70000 - 90000 € per year.
Wayve, located in London, is seeking a Staff ML Performance Engineer to optimize ML inference on edge devices. This full-time role includes responsibilities such as profiling bottlenecks in the inference stack and implementing optimisations in compilers and runtimes.
The ideal candidate has proven experience with production systems, strong proficiency in relevant tools like TensorRT and CUDA, and solid software engineering fundamentals.
The position offers a hybrid working model, allowing for flexibility between office and home.
Staff ML Inference Performance Engineer - Edge GPUs in London employer: Wayve
Wayve is an exceptional employer that fosters a dynamic and innovative work culture in the heart of London. With a strong emphasis on employee growth, we provide ample opportunities for professional development and collaboration on cutting-edge technology in machine learning. Our hybrid working model ensures flexibility, allowing you to balance your personal and professional life while contributing to meaningful projects that shape the future of edge computing.
StudySmarter Expert Advice🤫
We think this is how you could land Staff ML Inference Performance Engineer - Edge GPUs in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working with edge devices and ML inference. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to ML performance and optimisations. This is your chance to demonstrate your expertise with tools like TensorRT and CUDA.
✨Tip Number 3
Prepare for technical interviews by brushing up on your software engineering fundamentals. We recommend practising coding challenges and discussing your past experiences with production systems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Staff ML Inference Performance Engineer - Edge GPUs in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with ML inference and tools like TensorRT and CUDA. We want to see how your skills align 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 optimising ML performance on edge devices. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Problem-Solving Skills:In your application, mention specific challenges you've faced in production systems and how you tackled them. We appreciate candidates who can demonstrate their analytical thinking and technical prowess.
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 don’t miss out on any important updates from us!
How to prepare for a job interview at Wayve
✨Know Your Tech Inside Out
Make sure you’re well-versed in the tools mentioned in the job description, like TensorRT and CUDA. Brush up on your knowledge of ML inference and be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific bottlenecks you've encountered in production systems and how you optimised them. Use concrete examples to illustrate your thought process and the impact of your solutions.
✨Understand the Company’s Vision
Research Wayve and their approach to ML on edge devices. Being able to articulate how your skills align with their goals will show that you’re genuinely interested in the role and the company.
✨Practice for Technical Questions
Expect technical questions that test your understanding of compilers and runtimes. Practise coding challenges or system design questions related to ML inference to ensure you're sharp and ready to impress.
