At a Glance
- Tasks: Test and validate cutting-edge machine learning software for performance and reliability.
- Company: Join Graphcore, a leader in AI innovation based in Greater London.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Fast-paced, innovative team with exciting challenges ahead.
- Why this job: Be at the forefront of AI technology and make a real impact in the field.
- Qualifications: Strong ML experience, Python proficiency, and debugging skills required.
The predicted salary is between 60000 - 80000 £ per year.
Graphcore is seeking an experienced ML Engineer to join their team in Greater London. This role focuses on testing, validating, and benchmarking a complex machine learning software stack, ensuring performance, reliability, and correctness across modern AI workloads.
The ideal candidate will have strong machine learning experience, proficiency in Python, and skills in debugging and analytical reasoning. Experience with ML frameworks and Linux environments is essential. This position presents an exciting opportunity to work in a fast-paced, innovative environment.
Staff ML Benchmarking & Reliability Engineer in London employer: graphcore
Graphcore is an exceptional employer that fosters a dynamic and innovative work culture in the heart of Greater London. Employees benefit from a collaborative environment that encourages professional growth through continuous learning opportunities and exposure to cutting-edge technology in machine learning. With a focus on performance and reliability, team members are empowered to make meaningful contributions to groundbreaking AI projects, making it a rewarding place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Staff ML Benchmarking & Reliability Engineer in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Graphcore on LinkedIn or attend industry meetups. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your machine learning projects. This is a great way to demonstrate your proficiency in Python and ML frameworks, making you stand out.
✨Tip Number 3
Practice makes perfect! Brush up on your debugging and analytical reasoning skills. Consider mock interviews with friends or use online platforms to simulate technical interviews related to ML.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have insider tips and updates on the hiring process that can help you along the way.
We think you need these skills to ace Staff ML Benchmarking & Reliability Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning and Python. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your background makes you a perfect fit. We love seeing genuine enthusiasm for what we do.
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled complex problems in ML or debugging. We’re looking for analytical reasoning, so share those experiences that demonstrate your thought process!
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 this exciting opportunity. Don’t miss out!
How to prepare for a job interview at graphcore
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts and frameworks. Be ready to discuss your experience with different ML models and how you've applied them in real-world scenarios. This will show that you’re not just familiar with the theory but can also implement it effectively.
✨Python Proficiency is Key
Since Python is a must-have for this role, practice coding problems and be prepared to demonstrate your skills during the interview. You might be asked to solve a problem on the spot, so make sure you’re comfortable with debugging and writing clean, efficient code.
✨Familiarise Yourself with Benchmarking
Understand the principles of benchmarking and testing in machine learning. Be ready to discuss how you’ve approached performance validation in past projects. Having specific examples will help you stand out and show your analytical reasoning skills.
✨Get Comfortable with Linux
Since experience in Linux environments is essential, make sure you’re familiar with common commands and tools. If you have experience setting up ML environments or managing dependencies, be prepared to share those experiences as they’ll be relevant to the role.
