Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and operate cutting-edge AI infrastructure while automating workflows.
- Company: Join a forward-thinking tech company in Edinburgh with a collaborative spirit.
- Benefits: Competitive pay, flexible remote work, and opportunities for professional growth.
- Why this job: Make a real impact in the AI field and work with innovative technologies.
- Qualifications: Experience in AI Ops, MLOps, or DevOps with strong scripting skills.
- Other info: Dynamic role with potential for contract extension and career advancement.
The predicted salary is between 48000 - 72000 £ per year.
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 employer: WorkGenius Group
Contact Detail:
WorkGenius Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer
✨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 land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI infrastructure or MLOps. We love seeing real-world applications of your expertise, so make sure to highlight your hands-on experience with tools like Docker and Kubernetes.
✨Tip Number 3
Prepare for the technical interview! Brush up on your Linux skills and be ready to discuss automation and scripting in Python or Bash. We want to see how you tackle problems, so practice explaining your thought process clearly.
✨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 who are eager to dive into AI Ops and make an impact.
We think you need these skills to ace Artificial Intelligence Engineer
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. Keep it concise but impactful!
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 don’t hold back!
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, automation, and scripting in Python or Bash. The more specific examples you can provide about your past projects, the better!
✨Showcase Your Infrastructure Skills
Prepare to talk about your experience with distributed systems and compute-heavy environments. Highlight any work you've done with GPU-based systems and CI/CD pipelines. If you've used containers like Docker or Kubernetes, be sure to mention that too!
✨Demonstrate Your Problem-Solving Abilities
Think of scenarios where you've had to troubleshoot or optimise AI systems. Be ready to explain how you approached these challenges and what tools you used, especially if you have experience with monitoring and observability tools like Prometheus or Grafana.
✨Be Ready for Onsite Collaboration
Since this role requires being onsite in Edinburgh three days a week, express your enthusiasm for collaborating closely with data scientists and engineers. Share examples of how you've successfully partnered with others in previous roles to keep AI systems stable and fast.
