At a Glance
- Tasks: Design and deploy scalable AI solutions using Azure and Generative AI technologies.
- Company: Join a forward-thinking AI engineering team at iXceed Solutions in Greater London.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic work environment with a focus on collaboration and cutting-edge projects.
- Why this job: Be at the forefront of AI innovation and make a significant impact in the tech industry.
- Qualifications: 5+ years in machine learning, with expertise in MLOps, Docker, and Kubernetes.
The predicted salary is between 60000 - 84000 £ per year.
iXceed Solutions is looking for an experienced ML Engineer to join their AI engineering team in Greater London. The successful candidate will utilize their expertise in Azure, Generative AI, and Large Language Models (LLMs) to design and deploy scalable AI solutions.
The ideal candidate should have at least 5 years of experience in machine learning engineering, with a strong focus on MLOps and model deployment strategies. Familiarity with Docker and Kubernetes is essential for this role.
Azure GenAI/LLM Engineer — RAG, MLOps, K8s in London employer: ixceed solutions
iXceed Solutions is an exceptional employer that fosters a collaborative and innovative work culture in the heart of Greater London. With a strong emphasis on employee growth, we offer continuous learning opportunities and the chance to work with cutting-edge technologies in AI and machine learning. Our commitment to work-life balance and a supportive environment makes us an attractive choice for professionals seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Azure GenAI/LLM Engineer — RAG, MLOps, K8s in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. 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 Azure, Generative AI, and LLMs. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on MLOps and deployment strategies. Be ready to discuss your experience with Docker and Kubernetes, as these are key for the role we're looking at.
✨Tip Number 4
Don't forget to 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 that extra step!
We think you need these skills to ace Azure GenAI/LLM Engineer — RAG, MLOps, K8s in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Azure, Generative AI, and LLMs. We want to see how your skills align with the role, so don’t be shy about showcasing your MLOps expertise and any relevant projects you've worked on.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI engineering and how your background makes you a perfect fit for our team. We love hearing about your journey and what drives you in this field.
Showcase Your Technical Skills:Don’t forget to mention your familiarity with Docker and Kubernetes. We’re looking for someone who can hit the ground running, so highlight any hands-on experience you have with these tools in your application.
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 the role. Plus, it gives you a chance to explore more about our company culture!
How to prepare for a job interview at ixceed solutions
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of Azure, Generative AI, and Large Language Models. Be ready to discuss specific projects where you've implemented these technologies, as well as any challenges you faced and how you overcame them.
✨Showcase Your MLOps Experience
Prepare to talk about your experience with MLOps and model deployment strategies. Have examples ready that demonstrate your ability to streamline processes and improve efficiency in deploying machine learning models.
✨Docker and Kubernetes are Key
Since familiarity with Docker and Kubernetes is essential, be prepared to discuss how you've used these tools in past projects. Highlight any specific instances where they played a crucial role in your work.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s current projects, their approach to AI solutions, and how they envision the role evolving. This shows your genuine interest and helps you assess if it's the right fit for you.
