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- Tasks: Develop and optimise AI models while collaborating with top-notch teams.
- Company: Leading tech company at the forefront of AI innovation.
- Benefits: Flexible working, competitive pay, and mental wellbeing support.
- Why this job: Join a dynamic team and shape the future of AI technology.
- Qualifications: Experience in machine learning and a passion for AI.
- Other info: Engage with the AI community and enjoy excellent career growth.
The predicted salary is between 43200 - 72000 £ per year.
A tech company specializing in AI is seeking a Senior Machine Learning Engineer to advance AI technology by developing and optimising models tailored to their hardware. This role involves implementing machine learning techniques, collaborating with software and research teams, and engages with the AI community.
The company offers competitive benefits including flexible working and support for mental wellbeing. Applicants must have the right to work in the UK.
Senior ML Engineer, Large-Scale AI Systems 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 Systems in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI community, attend meetups, and connect with current employees at the company. You never know who might give you a heads-up about an opportunity or refer you directly!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those that demonstrate your ability to optimise models for hardware. This will make you stand out when chatting with potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML techniques and algorithms. Practice coding challenges and be ready to discuss your past projects in detail. We want you to shine during those interviews!
✨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 and engaged with our company.
We think you need these skills to ace Senior ML Engineer, Large-Scale AI Systems in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning and AI systems. We want to see how you've developed and optimised models in the past, so don’t hold back on those details!
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 your skills align with our mission. Let us know how you can contribute to our team and the AI community.
Showcase Collaboration Skills: Since this role involves working closely with software and research teams, highlight any previous experiences where you’ve successfully collaborated. We love seeing teamwork in action!
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 graphcore
✨Know Your Models Inside Out
Make sure you’re well-versed in the machine learning models relevant to the role. Be prepared to discuss your experience with developing and optimising these models, especially in relation to hardware. Brush up on any recent advancements in AI that could be applicable.
✨Showcase Collaboration Skills
This role involves working closely with software and research teams, so be ready to share examples of past collaborations. Highlight how you’ve effectively communicated complex ideas and contributed to team projects, as this will demonstrate your ability to fit into their collaborative culture.
✨Engage with the AI Community
Since the company values engagement with the AI community, mention any conferences, workshops, or online forums you’ve participated in. Discussing your involvement can show your passion for the field and your commitment to staying updated with industry trends.
✨Prepare Questions About Their Tech Stack
Research the company’s tech stack and prepare insightful questions about it. This shows your genuine interest in the role and helps you understand how you can contribute to their projects. It also gives you a chance to assess if their technology aligns with your expertise.
