At a Glance
- Tasks: Test and benchmark complex ML software, ensuring performance and correctness.
- Company: Join Graphcore, a leader in AI technology and innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Fast-paced environment with exciting challenges and career advancement opportunities.
- Why this job: Be at the forefront of AI, working with cutting-edge technologies and talented teams.
- Qualifications: Strong experience in machine learning, Python proficiency, and understanding of AI concepts.
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 in London 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 the chance to collaborate with leading experts in the field, making it an ideal environment for growth and meaningful contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Senior ML Benchmarking & QA Engineer in London
✨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! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Senior ML Benchmarking & QA Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning systems and Python. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about ML benchmarking and QA. We love seeing candidates who can express their enthusiasm for the field and our mission.
Showcase Your Technical Skills:When filling out your application, be specific about your technical expertise. Mention any industry-standard ML frameworks you’ve worked with, as this will help us understand your fit for the 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. Plus, it’s super easy!
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 prepared to discuss how you handle feedback and integrate it into your work.
