Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and operate cutting-edge AI infrastructure for real-world applications.
- Company: Join a forward-thinking tech company in Edinburgh with a focus on innovation.
- Benefits: Competitive pay, flexible remote work, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology and make a tangible impact.
- Qualifications: Experience in AI Ops, MLOps, or Infrastructure Engineering is essential.
- Other info: Dynamic team environment with potential for contract extension.
The predicted salary is between 48000 - 72000 £ per year.
AI Infrastructure / AI Operations Engineer (Contract)
Location: Edinburgh, UK
Onsite: 3 days per week – mandatory / Remote
Start: ASAP
Duration: 12-24 months (extension very likely)
Language: English (must-have)
What you’ll do:
- Build and operate AI / ML infrastructure used in production
- Support model deployment, monitoring and scaling
- Automate workflows around training, evaluation and deployment
- Work with GPU-based systems, distributed compute and CI/CD pipelines
- Partner closely with data scientists and engineers to keep AI systems stable and fast
What you bring:
- Strong background in AI Ops, MLOps, DevOps or Infrastructure Engineering
- Hands-on experience with Linux, automation, scripting (Python/Bash)
- Experience with distributed systems and compute-heavy environments
- Familiarity with containers & orchestration (Docker, Kubernetes or similar)
- Comfortable operating onsite in Edinburgh 3x/week
Nice to have:
- GPU / CUDA experience
- Exposure to HPC or large-scale AI platforms
- Monitoring & observability tools (Prometheus, Grafana, etc.)
Artificial Intelligence Engineer in Edinburgh employer: WorkGenius Group
Contact Detail:
WorkGenius Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML space on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to AI Ops or MLOps. We love seeing hands-on experience, so make sure to highlight any automation scripts or infrastructure setups you've worked on.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of distributed systems and CI/CD pipelines. We want to see you shine when discussing your experience with tools like Docker and Kubernetes.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate candidates ready to dive into the world of AI infrastructure.
We think you need these skills to ace Artificial Intelligence Engineer in Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI Ops, MLOps, and DevOps. We want to see how your skills align with the job description, so don’t be shy about showcasing your hands-on experience with Linux and automation!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI infrastructure and how your background makes you a perfect fit for our team. Let us know what excites you about this role!
Showcase Relevant Projects: If you've worked on any projects involving distributed systems or GPU-based environments, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions of your work!
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 WorkGenius Group
✨Know Your AI Ops Inside Out
Make sure you brush up on your knowledge of AI Ops, MLOps, and DevOps. Be ready to discuss your hands-on experience with Linux and automation tools like Python or Bash. Prepare examples of how you've built or operated AI infrastructure in the past.
✨Showcase Your Technical Skills
Be prepared to dive deep into your technical skills, especially around distributed systems and GPU-based environments. Have specific examples ready that demonstrate your experience with containers and orchestration tools like Docker and Kubernetes.
✨Demonstrate Collaboration
Since you'll be partnering closely with data scientists and engineers, think of instances where you've successfully collaborated in a team setting. Highlight how you’ve contributed to keeping AI systems stable and fast through teamwork.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company's AI infrastructure and their approach to model deployment and monitoring. This shows your genuine interest in the role and helps you understand if it's the right fit for you.
