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- Tasks: Develop and optimise AI models for cutting-edge hardware, focusing on scalability and performance.
- Company: Leading AI technology firm in the UK with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join us to make a tangible impact in the rapidly evolving AI landscape.
- Qualifications: Strong background in AI, deep learning frameworks, and excellent communication skills.
- Other info: Collaborative environment with cross-functional teams driving technological advancements.
The predicted salary is between 43200 - 72000 £ per year.
A leading AI technology firm in the UK is looking for a Senior Machine Learning Engineer to drive advancements in AI technology. In this role, you will develop and optimise AI models for our cutting-edge hardware, focusing on scalability and performance.
Collaborating with cross-functional teams, this engineer will innovate and differentiate our technology in a rapidly evolving landscape. The position requires strong technical and communication skills, along with a solid background in AI and deep learning frameworks. Join us to make a tangible impact in AI!
Senior ML Engineer: Large-Scale AI & Distributed Training in London employer: graphcore
Contact Detail:
graphcore Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer: Large-Scale AI & Distributed Training in London
✨Tip Number 1
Network like a pro! Reach out to people in the AI and ML community, attend meetups, and connect 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 projects, especially those related to AI and deep 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 algorithms and data structures. Practice coding challenges on platforms like LeetCode or HackerRank to sharpen your problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Senior ML Engineer: Large-Scale AI & Distributed Training in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI and deep learning frameworks. 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 AI and how you can contribute to our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Technical Skills: In your application, be specific about the tools and technologies you’ve worked with. Mention any experience with large-scale AI models and distributed training, as this will really catch our eye!
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 – just a few clicks and you’re done!
How to prepare for a job interview at graphcore
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI models and deep learning frameworks. Be ready to discuss specific projects you've worked on, the challenges you faced, and how you optimised performance. This will show that you’re not just familiar with the theory but have practical experience too.
✨Showcase Your Collaboration Skills
Since this role involves working with cross-functional teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight any experiences where you’ve had to communicate complex technical concepts to non-technical team members. This will demonstrate your ability to bridge gaps and work effectively with others.
✨Prepare for Technical Questions
Expect some tough technical questions during the interview. Brush up on algorithms, scalability issues, and distributed training techniques. Practising coding problems or discussing your thought process on solving real-world ML challenges can really set you apart from other candidates.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the company’s current projects, their approach to innovation, or how they measure success in AI technology. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.
