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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 professional 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: 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 in Livingston employer: WorkGenius Group
Contact Detail:
WorkGenius Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in Livingston
✨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 get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to AI Ops or MLOps. We love seeing real-world applications of your work, so make sure to highlight any automation or deployment processes you've tackled.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge, especially around Linux, Python, and distributed systems. We want to see you shine, so practice explaining your thought process and problem-solving skills.
✨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’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 Livingston
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of an AI Infrastructure Engineer. Highlight your experience with AI Ops, MLOps, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Showcase Your Skills: In your application, don’t just list your skills—show us how you’ve used them! Whether it’s automating workflows or working with GPU-based systems, give us examples that demonstrate your hands-on experience.
Be Clear and Concise: When writing your cover letter, keep it clear and to the point. We appreciate straightforward communication, so make sure you get across why you’re a great fit for the role without rambling on.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at WorkGenius Group
✨Know Your AI Infrastructure
Make sure you brush up on your knowledge of AI and ML infrastructure. Be ready to discuss your hands-on experience with Linux, automation, and scripting in Python or Bash. Highlight specific projects where you've built or operated AI systems, as this will show your practical understanding.
✨Showcase Your Collaboration Skills
Since the role involves partnering closely with data scientists and engineers, be prepared to share examples of how you've successfully collaborated in the past. Discuss any challenges you faced and how you overcame them, demonstrating your ability to work well in a team.
✨Familiarise Yourself with Tools
Get comfortable with the tools mentioned in the job description, like Docker, Kubernetes, and monitoring tools such as Prometheus and Grafana. If you have experience with GPU/CUDA or large-scale AI platforms, make sure to mention it, as it could set you apart from other candidates.
✨Prepare for Technical Questions
Expect technical questions related to distributed systems and CI/CD pipelines. Brush up on your knowledge in these areas and be ready to explain your thought process when solving problems. Practising common interview questions can help you articulate your expertise clearly.
