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- Tasks: Develop high-performance machine learning kernels for innovative AI hardware.
- Company: Join a forward-thinking tech company in the UK.
- Benefits: Enjoy flexible working, comprehensive health plans, and more.
- Other info: Collaborative environment with strong focus on problem-solving.
- Why this job: Make an impact in AI while working with cutting-edge technology.
- Qualifications: Bachelor's or Master's degree in relevant fields and C/C++11 experience.
The predicted salary is between 28000 - 38000 £ per year.
An innovative tech company in the UK is seeking a Graduate Software Engineer to develop high-performance machine learning kernels for cutting-edge AI hardware. Candidates should possess a Bachelor's or Master's degree in relevant fields, experience in C/C++11, and an understanding of numerical methods.
The role involves optimizing compute kernels for ML applications and requires collaboration and strong problem-solving skills.
This position offers a range of benefits including flexible working and comprehensive health plans.
Graduate ML Kernel Engineer (Performance Focus) employer: graphcore
Contact Detail:
graphcore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate ML Kernel Engineer (Performance Focus)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups or webinars, and connect with fellow graduates. 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, especially those involving C/C++11 and machine learning. 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 problem-solving skills. Practice coding challenges and be ready to discuss numerical methods and optimising compute kernels. We recommend using platforms that offer mock interviews to get comfortable.
✨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 Graduate ML Kernel Engineer (Performance Focus)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with C/C++11 and any relevant projects you've worked on. We want to see how you can apply your knowledge to develop high-performance machine learning kernels!
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect the specific skills and experiences that match the job description. This shows us you’re genuinely interested in the role and understand what we’re looking for.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your achievements and experiences are easy to read and understand.
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 from our team!
How to prepare for a job interview at graphcore
✨Know Your Tech Inside Out
Make sure you brush up on your C/C++11 skills and understand numerical methods thoroughly. Be ready to discuss how you've applied these in past projects or coursework, as this will show your technical prowess and readiness for the role.
✨Showcase Your Problem-Solving Skills
Prepare to tackle some technical problems during the interview. Practice explaining your thought process clearly and logically. This will demonstrate not just your problem-solving abilities but also your communication skills, which are crucial for collaboration.
✨Understand the Company’s Vision
Research the company’s focus on AI hardware and their innovative projects. Being able to discuss how your skills align with their goals will impress the interviewers and show that you're genuinely interested in contributing to their success.
✨Ask Insightful Questions
Prepare a few thoughtful questions about the team dynamics, the technologies they use, or the challenges they face in optimising ML kernels. This shows your enthusiasm for the role and helps you gauge if the company is the right fit for you.