At a Glance
- Tasks: Test, validate, and benchmark cutting-edge ML software in a dynamic 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: Fast-paced environment with opportunities for professional growth.
- Why this job: Make an impact in the AI field while collaborating with talented teams.
- Qualifications: Strong foundation in AI concepts and experience with PyTorch or TensorFlow.
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 employer: graphcore
Graphcore 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 offer competitive salaries, flexible working arrangements, and generous benefits, making it an ideal place for those passionate about advancing their careers in machine learning and AI. Join us to be part of a collaborative team that values creativity and excellence in technology.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML QA Engineer — Benchmarking & Performance
✨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 work with AI frameworks like PyTorch or TensorFlow. This can really set you apart and give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML concepts and testing strategies. Practise common interview questions and maybe even do some mock interviews with friends or mentors.
✨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 are proactive about their job search.
We think you need these skills to ace Senior ML QA Engineer — Benchmarking & Performance
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 AI frameworks like PyTorch and TensorFlow. Be ready to discuss your hands-on experience with these tools, as well as any specific projects you've worked on that showcase your skills in testing and validating ML software.
✨Understand Benchmarking Techniques
Familiarise yourself with various benchmarking techniques used in machine learning. Be prepared to explain how you would approach performance testing and validation, and share examples of how you've successfully implemented these techniques in past roles.
✨Collaborate Like a Pro
Since you'll be working closely with software teams, highlight your collaboration skills. Think of examples where you've effectively communicated with cross-functional teams to achieve project goals, and be ready to discuss how you handle feedback and adapt to fast-paced environments.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to ML software development and their expectations for the role. This shows your genuine interest in the position and helps you gauge if it's the right fit for you. Plus, it gives you a chance to demonstrate your knowledge of the industry!
