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- Tasks: Build production-grade AI systems for analysing clinical trial data in pharma R&D.
- Company: Large consultancy with a dynamic and innovative environment.
- Benefits: Competitive salary, hybrid working, and additional benefits.
- Why this job: Join a cutting-edge AI team and make a real impact in healthcare.
- Qualifications: 1-2 years of LLM deployment experience and strong Python skills.
- Other info: Collaborative culture with opportunities for professional growth.
The predicted salary is between 70000 - 80000 £ per year.
A large consultancy is seeking an experienced LLM Engineer to build production-grade AI systems analyzing clinical trial data for pharmaceutical R&D. The ideal candidate will have 1-2 years of experience deploying LLM solutions, strong Python skills, and familiarity with orchestration frameworks.
The role involves working closely in an AI team within a dynamic organization, with a hybrid working structure requiring 2-3 days in the office each week. Competitive salary of £70,000 - £80,000 plus benefits.
Production LLM Engineer for Pharma R&D AI Systems in City of London employer: Avanti Recruitment
Contact Detail:
Avanti Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Production LLM Engineer for Pharma R&D AI Systems in City of London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in pharma R&D AI. A friendly chat can lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your LLM projects and any relevant work you've done with clinical trial data. This will help you stand out during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on Python and orchestration frameworks. We recommend doing mock interviews with friends or using online platforms to simulate the real deal.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications that way!
We think you need these skills to ace Production LLM Engineer for Pharma R&D AI Systems in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with LLM solutions and Python skills. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your skills can contribute to our AI team. Keep it engaging and personal – we love a bit of personality!
Showcase Your Projects: If you've worked on any cool projects related to clinical trial data or orchestration frameworks, make sure to mention them. We’re keen to see what you’ve done and how it relates to the work we do at StudySmarter.
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 Avanti Recruitment
✨Know Your LLMs Inside Out
Make sure you brush up on your knowledge of large language models. Be ready to discuss your experience deploying LLM solutions, including any specific projects you've worked on. Highlight your understanding of how these models can be applied in analysing clinical trial data.
✨Show Off Your Python Skills
Since strong Python skills are a must for this role, prepare to demonstrate your coding abilities. You might be asked to solve a problem or explain your approach to a project. Practise coding challenges and be ready to discuss libraries and frameworks you’ve used.
✨Familiarity with Orchestration Frameworks
Be prepared to talk about your experience with orchestration frameworks. Whether it’s Kubernetes, Airflow, or something else, know the ins and outs of how these tools help in deploying AI systems. Share examples of how you’ve used them in past projects.
✨Embrace the Hybrid Work Culture
Since the role requires a hybrid working structure, be ready to discuss how you manage your time and productivity in both office and remote settings. Share your strategies for collaboration and communication within a team, especially in a dynamic environment.
