At a Glance
- Tasks: Test and optimise AI workloads to enhance ML software performance.
- Company: Join Graphcore, a leader in innovative ML technology.
- Benefits: Enjoy a supportive environment with opportunities for professional growth.
- Other info: Collaborative team culture focused on innovation.
- Why this job: Make a real impact on cutting-edge AI projects and technologies.
- Qualifications: Strong background in ML systems and proficiency in Python.
The predicted salary is between 50000 - 70000 £ per year.
Graphcore is looking for a skilled Machine Learning Quality Assurance Engineer to enhance the performance and reliability of our ML software. In this role, you will be an integral part of our team, testing and optimizing complex AI workloads across various hardware environments.
The position requires a strong background in ML systems, extensive use of Python, and experience with industry-standard frameworks like PyTorch and TensorFlow. The role offers a supportive work environment focused on innovation and professional growth.
ML QA Engineer: Performance, Testing & Benchmarking in London employer: AgileGrid Solutions
Graphcore is an excellent employer that fosters a culture of innovation and collaboration, making it an ideal place for a Machine Learning Quality Assurance Engineer to thrive. With a strong emphasis on professional development, employees are encouraged to enhance their skills in a supportive environment while working on cutting-edge AI technologies. Located in a vibrant tech hub, the company offers unique opportunities to engage with industry leaders and contribute to groundbreaking advancements in machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land ML QA Engineer: Performance, Testing & Benchmarking in London
✨Tip Number 1
Network like a pro! Reach out to folks in the ML community on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with Python, PyTorch, and TensorFlow. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on performance testing and benchmarking techniques. Be ready to discuss your past experiences and how you've optimised ML workloads in different environments.
✨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 ML QA Engineer: Performance, Testing & Benchmarking in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with ML systems and frameworks like PyTorch and 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 QA and how your background makes you a perfect fit for our team. Let us know what excites you about working at Graphcore.
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled challenges in performance testing or benchmarking. We love seeing candidates who can think critically and innovate in their approach to ML workloads.
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 the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at AgileGrid Solutions
✨Know Your ML Basics
Make sure you brush up on your machine learning fundamentals. Understand key concepts, algorithms, and how they apply to performance testing. Being able to discuss these topics confidently will show that you're not just familiar with the tools but also understand the underlying principles.
✨Showcase Your Python Skills
Since Python is a must-have for this role, be prepared to demonstrate your coding skills. You might be asked to solve a problem or debug a piece of code during the interview. Practise common Python tasks related to ML, and be ready to explain your thought process as you work through them.
✨Familiarise Yourself with Frameworks
Get comfortable with industry-standard frameworks like PyTorch and TensorFlow. Be ready to discuss your experience with these tools, including any specific projects you've worked on. If possible, bring examples of how you've optimised ML workloads in the past using these frameworks.
✨Prepare Questions About the Role
Interviews are a two-way street, so come armed with questions about the team, the projects you'll be working on, and the company culture. This shows your genuine interest in the position and helps you assess if it's the right fit for you. Plus, it gives you a chance to learn more about their approach to innovation and professional growth.
