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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 career growth.
- Why this job: Make an impact in the AI field and work with innovative technologies.
- Qualifications: Experience in AI Ops, MLOps, or Infrastructure Engineering is essential.
- Other info: Enjoy a dynamic work 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 Scotland employer: WorkGenius Group
Contact Detail:
WorkGenius Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in Scotland
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML community, attend meetups or webinars, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI infrastructure or MLOps. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of distributed systems and CI/CD pipelines. Practice coding challenges and be ready to discuss your past experiences with automation and scripting.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team directly.
We think you need these skills to ace Artificial Intelligence Engineer in Scotland
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 relevant projects or technologies you've worked with!
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 engaging – we love a good story!
Show Off Your Technical Skills: When detailing your experience, be specific about the tools and technologies you've used, like Python, Docker, or Kubernetes. We’re keen on seeing your hands-on experience, so don’t hold back on the details!
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 a few clicks and you’re done!
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 experience with distributed systems and GPU-based environments. Bring specific examples of projects where you've worked with containers and orchestration tools like Docker or Kubernetes. This will show that you can hit the ground running.
✨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, as teamwork is key in this role.
✨Prepare for Practical Questions
Expect some technical questions or scenarios related to model deployment, monitoring, and scaling. Practise explaining your thought process clearly and concisely. This will help you demonstrate your problem-solving skills and technical expertise effectively.
