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- Tasks: Design and build LLM-powered applications while managing language-model systems.
- Company: Leading AI development company in Greater London with a focus on innovation.
- Benefits: Competitive salary and the opportunity to work on impactful AI solutions.
- Why this job: Join a dynamic team and shape the future of AI technology.
- Qualifications: Strong Python skills and experience with production ML infrastructure.
The predicted salary is between 36000 - 60000 £ per year.
A leading AI development company in Greater London is seeking an LLM Engineer to take ownership of language-model systems from training through to deployment. You will design and build LLM-powered applications while collaborating closely with senior researchers. Strong Python fundamentals and experience with production ML infrastructure are required. This role offers competitive salary and the chance to work on impactful AI solutions.
LLM Engineer — Build & Deploy Production-Grade AI in London employer: Bluebird
Contact Detail:
Bluebird Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land LLM Engineer — Build & Deploy Production-Grade AI in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI community, attend meetups, and connect with professionals 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 LLM projects and any relevant applications you've built. This is your chance to demonstrate your Python prowess and production ML infrastructure experience in a tangible way.
✨Tip Number 3
Prepare for those interviews! Brush up on common technical questions related to LLMs and be ready to discuss your past experiences. Practising with a friend or using mock interview platforms can really help us nail it.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of exciting opportunities waiting for you. Plus, applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace LLM Engineer — Build & Deploy Production-Grade AI in London
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your Python fundamentals in your application. We want to see how you've used Python in real-world projects, especially in relation to ML infrastructure.
Talk About Your Experience: Don’t just list your previous jobs; tell us about the specific projects you’ve worked on. We love hearing about your hands-on experience with language-model systems and how you’ve contributed to their success.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and enthusiasm for the role.
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 us!
How to prepare for a job interview at Bluebird
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python in detail, especially how you've used it in machine learning projects. Practising coding challenges can also help you demonstrate your problem-solving abilities.
✨Understand LLMs and Their Applications
Familiarise yourself with the latest advancements in language models and their applications. Be prepared to discuss specific projects where you've implemented LLMs or similar technologies. Showing that you’re up-to-date with industry trends will impress the interviewers.
✨Showcase Your Production ML Experience
Since this role requires experience with production ML infrastructure, be ready to talk about your past experiences in deploying machine learning models. Discuss any tools or frameworks you've used, and highlight any challenges you faced and how you overcame them.
✨Collaborate and Communicate
This position involves working closely with senior researchers, so emphasise your teamwork and communication skills. Prepare examples of how you've successfully collaborated on projects in the past, and be ready to discuss how you handle feedback and contribute to a team environment.
