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 employer: AgileGrid Solutions
Graphcore is an excellent employer, offering a dynamic and innovative work culture that prioritises professional growth and collaboration. As a Machine Learning Quality Assurance Engineer, you will benefit from a supportive environment that encourages creativity and the exploration of cutting-edge technologies, all while being part of a team dedicated to pushing the boundaries of AI performance. Located in a vibrant tech hub, employees enjoy access to numerous networking opportunities and resources that foster both personal and career development.
StudySmarter Expert Advice🤫
We think this is how you could land ML QA Engineer: Performance, Testing & Benchmarking
✨Tip Number 1
Network like a pro! Reach out to folks in the ML community, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings at companies like Graphcore.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, PyTorch, or 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 technical interviews by brushing up on your ML knowledge and testing strategies. Practice coding challenges and be ready to discuss your past experiences with performance testing and benchmarking.
✨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 ML QA Engineer: Performance, Testing & Benchmarking
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, include examples of how you've tackled challenges in performance testing or benchmarking. We love seeing candidates who can think critically and innovate solutions in complex environments.
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’s super easy!
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 problems or even write snippets of code during the interview. Practise common ML-related coding challenges to ensure you're ready to impress.
✨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. Highlighting your hands-on experience will set you apart from other candidates.
✨Prepare Questions About the Role
Interviews are a two-way street, so come armed with thoughtful 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.
