At a Glance
- Tasks: Build cutting-edge AI tools and develop APIs for enterprise solutions.
- Company: Join EPAM Systems, a leader in innovative technology.
- Benefits: Enjoy stock options, medical benefits, and endless learning opportunities.
- Other info: Be part of a dynamic team with great career growth potential.
- Why this job: Make an impact in AI while working in a hybrid, tech-savvy environment.
- Qualifications: Experience in machine learning and backend engineering is a plus.
The predicted salary is between 60000 - 80000 £ per year.
EPAM Systems is seeking a Machine Learning Engineer to join the team in London, United Kingdom, in a hybrid working mode. This role involves contributing to an enterprise AI program by building MCP Servers and Tools, developing APIs, and implementing evaluation mechanisms for language models.
The successful candidate will work in a highly technical environment focusing on backend engineering, AI architecture, and integration to deliver scalable AI solutions.
Perks include a stock purchase plan, medical benefits, and various learning opportunities.
Enterprise AI Engineer — LLM, MCP, Kubernetes (Hybrid) employer: EPAM Systems
EPAM Systems is an excellent employer for those looking to thrive in the cutting-edge field of AI engineering. With a hybrid working model based in London, employees benefit from a collaborative and innovative work culture that prioritises professional growth through continuous learning opportunities. The company also offers attractive perks such as a stock purchase plan and comprehensive medical benefits, making it a rewarding place to advance your career in technology.
StudySmarter Expert Advice🤫
We think this is how you could land Enterprise AI Engineer — LLM, MCP, Kubernetes (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at EPAM Systems. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got projects or contributions related to AI, Kubernetes, or backend engineering, make sure to highlight them in conversations. We want to see your passion and expertise shine through!
✨Tip Number 3
Prepare for technical interviews by brushing up on relevant concepts. Dive into LLMs, APIs, and evaluation mechanisms. We know it sounds daunting, but practice makes perfect, and you'll feel more confident when the time comes.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Enterprise AI Engineer — LLM, MCP, Kubernetes (Hybrid)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in AI, backend engineering, and any specific tools like Kubernetes. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about enterprise AI and how your background makes you a perfect fit for our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects:If you've worked on any projects related to language models or APIs, make sure to mention them! We’re interested in seeing practical examples of your work, so include links or descriptions that demonstrate your expertise.
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’s super easy – just follow the prompts!
How to prepare for a job interview at EPAM Systems
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like MCP Servers, APIs, and Kubernetes. Brush up on your knowledge of language models and be ready to discuss how you've used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to tackle hypothetical scenarios or technical challenges during the interview. Think about how you would approach building scalable AI solutions and be ready to explain your thought process clearly.
✨Demonstrate Team Collaboration
Since this role involves working in a team, be prepared to share examples of how you’ve successfully collaborated with others in a technical environment. Highlight any experience you have in cross-functional teams or agile methodologies.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about the current projects they’re working on or how they measure the success of their AI solutions. This shows you’re genuinely interested and engaged.
