At a Glance
- Tasks: Test and benchmark complex ML software stacks to ensure performance and correctness.
- Company: Join Graphcore, a leader in AI technology with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Fast-paced environment with collaboration across software and hardware teams.
- Why this job: Be at the forefront of AI technology and make a real impact in the industry.
- Qualifications: Strong experience in machine learning systems and proficiency in Python.
The predicted salary is between 60000 - 80000 £ per year.
Graphcore is seeking an experienced ML Engineer to focus on testing and benchmarking a complex ML software stack. The ideal candidate will have strong experience with machine learning systems, a solid understanding of AI concepts, and proficiency in Python.
You will work with industry-standard ML frameworks in a fast-paced environment, ensuring performance and correctness across AI workloads while collaborating closely with software and hardware teams.
Senior ML Benchmarking & QA Engineer employer: graphcore
Graphcore is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those passionate about machine learning and AI. Located in a vibrant tech hub, we offer competitive benefits, continuous professional development opportunities, and a collaborative environment where your contributions directly impact cutting-edge technology. Join us to be part of a forward-thinking team that values creativity and excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML Benchmarking & QA Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. 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 ML projects, benchmarks, and any relevant work you've done. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML scenarios and be ready to discuss your experience with Python and AI concepts in detail.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from candidates who are excited about joining us at StudySmarter. It shows initiative and enthusiasm!
We think you need these skills to ace Senior ML Benchmarking & QA Engineer
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with machine learning systems and AI concepts in your application. We want to see how your skills align with the role, so don’t hold back!
Be Specific About Your Experience:When detailing your past work, be specific about the ML frameworks you've used and any benchmarking or QA processes you've implemented. This helps us understand your hands-on experience.
Tailor Your Application:Customise your CV and cover letter to reflect the job description. Use keywords from the posting to show that you’re a perfect fit for the Senior ML Benchmarking & QA Engineer role.
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 position!
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 various ML systems 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, be prepared to showcase your coding skills. You might be asked to solve problems or even write snippets of code during the interview. Practise common algorithms and data structures in Python to demonstrate your proficiency.
✨Benchmarking Basics
Understand the principles of benchmarking in ML. Be ready to explain how you would approach testing and evaluating the performance of ML models. Discuss any tools or methodologies you’ve used in the past to ensure accuracy and efficiency in your benchmarks.
✨Collaboration is Crucial
This role involves working closely with both software and hardware teams, so highlight your teamwork skills. Share examples of how you’ve successfully collaborated with cross-functional teams in previous roles, and be ready to discuss how you handle feedback and integrate it into your work.
