At a Glance
- Tasks: Test and validate ML software while benchmarking performance in a fast-paced environment.
- Company: Join Graphcore, a leader in AI technology based in London.
- Benefits: Enjoy a competitive salary, flexible working hours, and generous benefits.
- Other info: Collaborate with talented teams and thrive in a dynamic work culture.
- Why this job: Make an impact in the AI field by working with cutting-edge frameworks like PyTorch and TensorFlow.
- Qualifications: Strong foundation in AI concepts and hands-on experience with ML frameworks.
The predicted salary is between 60000 - 80000 £ per year.
Graphcore is seeking an experienced ML Engineer in London to focus on testing, validating, and benchmarking ML software. You will work with AI frameworks and collaborate with software teams in a fast-paced environment.
Ideal candidates will have a strong foundation in AI concepts and hands-on experience with frameworks like PyTorch or TensorFlow.
The position offers a competitive salary, flexible working, and generous benefits.
Senior ML QA Engineer — Benchmarking & Performance in London employer: graphcore
Graphcore is an exceptional employer, offering a dynamic work culture in the heart of London where innovation thrives. With a focus on employee growth, we provide ample opportunities for professional development alongside competitive salaries and flexible working arrangements, ensuring that our team members can achieve a rewarding work-life balance while contributing to cutting-edge AI advancements.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML QA Engineer — Benchmarking & Performance in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working at Graphcore or similar companies. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving benchmarking and performance testing. This will give you an edge and demonstrate your hands-on experience with frameworks like PyTorch or TensorFlow.
✨Tip Number 3
Prepare for technical interviews by brushing up on AI concepts and practical applications. We recommend doing mock interviews with friends or using online platforms 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 Senior ML QA Engineer — Benchmarking & Performance in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with AI frameworks like PyTorch or TensorFlow. 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 ML 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 Problem-Solving Skills:In your application, give examples of how you've tackled challenges in ML testing and validation. We’re looking for candidates who can think critically and adapt in a fast-paced environment, so let us know how you’ve done this before!
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, it’s super easy!
How to prepare for a job interview at graphcore
✨Know Your ML Frameworks
Make sure you brush up on your knowledge of PyTorch and TensorFlow. Be ready to discuss your hands-on experience with these frameworks, as well as any specific projects where you've tested or benchmarked ML software.
✨Understand AI Concepts
Familiarise yourself with key AI concepts that are relevant to the role. This could include topics like model evaluation metrics, overfitting, and performance optimisation. Being able to articulate these concepts will show your depth of understanding.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and your approach to testing ML software. Practice explaining your thought process clearly and concisely, as this will demonstrate your analytical abilities.
✨Show Your Collaborative Spirit
Since the role involves working closely with software teams, be prepared to discuss your experience in collaborative environments. Share examples of how you've successfully worked with others to achieve common goals, especially in fast-paced settings.
