At a Glance
- Tasks: Build and maintain a cutting-edge AI platform with Kubernetes and LLMOps tools.
- Company: Join a small, high-impact AI team driving innovation.
- Benefits: Competitive salary, full-time role, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on learning and development.
- Why this job: Make a real impact on AI innovation and work with experienced engineers.
- Qualifications: 2-4 years in Platform or DevOps Engineering, strong Kubernetes and Terraform skills.
The predicted salary is between 48000 - 72000 £ per year.
An exciting opportunity to join a small, high-impact AI team building an internal AI Platform that powers the next generation of intelligent products and services. You’ll work on cutting‑edge AI infrastructure, collaborate with experienced platform engineers, and make a real impact on how AI innovation scales across the organization.
What you’ll be doing:
- Building and maintaining a Kubernetes‑hosted AI platform (AKS)
- Deploying and managing LLMOps tools such as LiteLLM, Langflow, and Langfuse
- Implementing observability with Prometheus, Grafana, and Loki
- Managing infrastructure through Terraform, ArgoCD, and GitHub Actions
- Supporting internal AI applications including RAG, document processing, and internal AI assistants
What you’ll need:
- 2–4 years in Platform or DevOps Engineering (Azure preferred)
- Strong experience with Kubernetes, Docker, and Terraform
- Programming or scripting skills in Python or Go
- Familiarity with GitOps, Helm, and observability tools
- A learning mindset and interest in LLM operations
Seniority level: Mid‑Senior level
Employment type: Full-time
Job function: Information Technology
To apply, contact the recruiter or send a direct message through the Explore Group platform.
Machine Learning Engineer employer: Explore Group
Explore Group is an exceptional employer that fosters a collaborative and innovative work culture, perfect for those passionate about advancing mining technology. With a focus on employee growth, we offer opportunities for professional development and the chance to lead impactful projects in a dynamic environment. Located in a vibrant area, our team enjoys a supportive atmosphere that values creativity and mission-driven work.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and DevOps space on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get your foot in the door.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your projects related to Kubernetes, Docker, or Terraform. This gives potential employers a taste of what you can do and makes you stand out from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of LLMOps tools and observability practices. We recommend doing mock interviews with friends or using online platforms to get comfortable with the questions you might face.
✨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 are proactive about their job search!
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Kubernetes, Docker, and Terraform. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re excited about joining our AI team and how your background in Platform or DevOps Engineering makes you a perfect fit for this role.
Show Off Your Learning Mindset:We love candidates who are eager to learn! In your application, mention any recent courses, certifications, or personal projects related to LLMOps or observability tools that demonstrate your commitment to growth.
Apply Through Our Website:To make sure your application gets the attention it deserves, apply directly through our website. It’s the best way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Explore Group
✨Know Your Tech Stack
Make sure you’re well-versed in Kubernetes, Docker, and Terraform. Brush up on your programming skills in Python or Go, as these will likely come up during technical discussions. Being able to speak confidently about your experience with these tools will show that you’re ready to hit the ground running.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built or maintained AI platforms or worked with LLMOps tools. Highlight your role, the challenges you faced, and how you overcame them. This not only demonstrates your technical skills but also your problem-solving abilities.
✨Understand the Company’s Vision
Research the company’s AI initiatives and understand how their internal AI platform fits into their overall strategy. Being able to articulate how your skills can contribute to their goals will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the technologies they use, and their approach to AI innovation. This shows your genuine interest in the role and helps you assess if it’s the right fit for you too.
