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- Tasks: Deploy and integrate AI solutions into production with a focus on LLM systems.
- Company: Leading tech company in the UK with a high-growth environment.
- Benefits: Up to £125,000 salary, bonuses, stock options, and career growth.
- Why this job: Join a new team and make an impact in the exciting field of AI.
- Qualifications: Strong understanding of machine learning, LLMs, Python, and AWS experience.
The predicted salary is between 75000 - 125000 £ per year.
A leading tech company in the United Kingdom is seeking an Applied AI Engineer who will focus on deploying and integrating AI solutions into production. This role requires a strong understanding of machine learning and LLM systems, with hands-on experience in Python and AWS. The ideal candidate will collaborate with various teams to deliver reliable AI features. This is a fantastic opportunity to join a new team in a high-growth environment, offering up to £125,000 per annum plus bonuses and stock options.
Production AI Engineer — Deploy & Scale LLMs in London employer: Burns Sheehan
Contact Detail:
Burns Sheehan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Production AI Engineer — Deploy & Scale LLMs in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues 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 involving machine learning and LLMs. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to Python and AWS. Practise coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting opportunities, and applying directly can sometimes give you a better chance of landing that dream role. Let’s get you started!
We think you need these skills to ace Production AI Engineer — Deploy & Scale LLMs in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning and LLM systems. We want to see how your skills in Python and AWS can shine through, so don’t hold back on those relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for this role. Share your passion for AI and how you’ve successfully deployed solutions in the past. Keep it engaging and personal!
Showcase Your Collaboration Skills: Since this role involves working with various teams, make sure to mention any collaborative projects you've been part of. We love seeing how you can work well with others to deliver reliable AI features.
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 Burns Sheehan
✨Know Your AI Stuff
Make sure you brush up on your knowledge of machine learning and LLM systems. Be ready to discuss specific projects you've worked on, especially those involving Python and AWS. This will show that you have the hands-on experience they’re looking for.
✨Show Your Team Spirit
Since this role involves collaboration with various teams, be prepared to talk about your experience working in a team environment. Share examples of how you’ve successfully collaborated on projects and how you handle differing opinions or challenges within a team.
✨Prepare for Technical Questions
Expect some technical questions during the interview. Brush up on key concepts related to deploying and integrating AI solutions. Practising coding problems in Python or discussing AWS services can give you an edge and demonstrate your technical prowess.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the company’s approach to AI deployment or how they measure success in their AI projects. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.
