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- Tasks: Develop and optimise distributed systems for large-scale AI infrastructure.
- Company: Join a forward-thinking team in Edinburgh focused on AI innovation.
- Benefits: Enjoy a competitive salary and comprehensive benefits package.
- Other info: Permanent, on-site role with opportunities for professional growth.
- Why this job: Contribute to cutting-edge AI research and performance tuning.
- Qualifications: Relevant degree and experience with LLM inference frameworks required.
The predicted salary is between 60000 - 80000 £ per year.
Project People seeks an AI Systems Research Engineer for their Edinburgh team. This permanent, on-site role focuses on the development and optimization of distributed systems for large-scale AI infrastructure. The successful candidate will work on performance tuning of AI serving frameworks and contribute to innovative research.
Candidates should hold a relevant degree and have experience with LLM inference frameworks and distributed systems. A competitive salary and benefits package is offered.
Edinburgh AI Infra Architect: LLM Serving & Systems employer: Project People
Contact Detail:
Project People Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Edinburgh AI Infra Architect: LLM Serving & Systems
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and systems engineering space on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your work with LLM inference frameworks and distributed systems. We recommend including any projects or research that highlight your expertise – it’s a great way to stand out!
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of performance tuning and AI serving frameworks. We suggest doing mock interviews with friends or using online platforms to get comfortable with the questions you might face.
✨Tip Number 4
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 take the initiative to apply directly – it shows you’re serious about joining the team!
We think you need these skills to ace Edinburgh AI Infra Architect: LLM Serving & Systems
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with LLM inference frameworks and distributed systems. 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 infrastructure and how your background makes you a perfect fit for our Edinburgh team. Keep it engaging and personal!
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled challenges in performance tuning or system optimisation. We love seeing candidates who can think critically and innovate, so let us know how you’ve made an impact in previous roles.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our company culture there!
How to prepare for a job interview at Project People
✨Know Your AI Frameworks
Make sure you brush up on your knowledge of LLM inference frameworks. Be ready to discuss your experience with them and how you've optimised performance in the past. This will show that you're not just familiar with the technology, but that you can also apply it effectively.
✨Showcase Your Distributed Systems Experience
Prepare specific examples of projects where you've worked with distributed systems. Highlight any challenges you faced and how you overcame them. This will demonstrate your problem-solving skills and your ability to work in complex environments.
✨Research Project People
Take some time to learn about Project People and their current projects in AI infrastructure. Understanding their goals and challenges will help you tailor your answers and show that you're genuinely interested in the role and the company.
✨Ask Insightful Questions
Prepare thoughtful questions to ask at the end of the interview. Inquire about their approach to performance tuning or future projects they’re excited about. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.