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- Tasks: Deploy and integrate AI models into production systems and design LLM-powered workflows.
- Company: High-growth tech company in Greater London with a focus on innovation.
- Benefits: Competitive salary up to £125,000, bonus, stock options, and hybrid work model.
- Why this job: Join a cutting-edge team and shape the future of AI technology.
- Qualifications: Strong experience in machine learning, excellent Python skills, and familiarity with AWS and MLOps.
- Other info: Exciting opportunity for career growth in a dynamic environment.
The predicted salary is between 75000 - 125000 £ per year.
A high-growth technology company in Greater London is seeking an Applied AI Engineer who can deploy and integrate AI models into production systems. This role involves designing LLM-powered workflows and building APIs to realize AI-driven features.
Ideal candidates will have:
- Strong experience with machine learning systems
- Excellent Python skills
- Familiarity with AWS and MLOps
This position offers a hybrid work model with a competitive salary up to £125,000 plus bonus and stock options.
Applied AI Engineer: Production AI & MLOps Lead (Hybrid) employer: Burns Sheehan
Contact Detail:
Burns Sheehan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI Engineer: Production AI & MLOps Lead (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and MLOps space on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving LLMs and APIs. We want to see your work in action, so make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and machine learning concepts. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨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 take the initiative to connect directly with us.
We think you need these skills to ace Applied AI Engineer: Production AI & MLOps Lead (Hybrid)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with machine learning systems and Python in your application. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Take a moment to customise your CV and cover letter for this specific role. Mention your familiarity with AWS and MLOps, as these are key aspects we’re looking for in an Applied AI Engineer.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so make sure your passion for AI and tech shines through without unnecessary fluff.
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 this exciting opportunity in our hybrid work environment!
How to prepare for a job interview at Burns Sheehan
✨Know Your AI Models
Make sure you’re well-versed in the AI models you’ve worked with. Be ready to discuss how you’ve deployed and integrated these models into production systems, especially focusing on LLM-powered workflows.
✨Showcase Your Python Skills
Brush up on your Python knowledge before the interview. Prepare to demonstrate your coding skills, perhaps by solving a problem or discussing a project where you used Python to build APIs for AI-driven features.
✨Familiarise Yourself with MLOps
Since this role involves MLOps, it’s crucial to understand the best practices and tools in this area. Be prepared to talk about your experience with AWS and how you’ve managed machine learning systems in a production environment.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company’s approach to AI and MLOps. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
