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For Companies At a Glance
- Tasks: Build and operate cutting-edge AI/ML infrastructure for real-world applications.
- Company: Join a forward-thinking tech company in Edinburgh with a collaborative spirit.
- Benefits: Competitive pay, flexible remote work, and opportunities for skill development.
- 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 role with potential for contract extension and career growth.
The predicted salary is between 48000 - 72000 £ per year.
Location: Edinburgh, UK
Onsite: 3 days per week – mandatory / Remote
Start: ASAP
Duration: ***** 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 Cumberland employer: WorkGenius Group
Contact Detail:
WorkGenius Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Artificial Intelligence Engineer in Cumberland
✨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 related to AI Ops or MLOps. We love seeing real-world applications of your work, so don’t be shy about sharing your GitHub or any relevant demos.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge, especially around Linux, Python, and distributed systems. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨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 ready to dive into the world of AI infrastructure.
We think you need these skills to ace Artificial Intelligence Engineer in Cumberland
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’re considered for the role. Plus, it’s super easy!
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. 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 compute-heavy environments. Highlight any projects where you've worked with GPU-based systems or CI/CD pipelines. This is your chance to impress them with your technical prowess!
✨Familiarise Yourself with Containers
Since familiarity with containers and orchestration tools like Docker and Kubernetes is key, make sure you can talk about your experience with these technologies. If you’ve automated workflows around training and deployment, have those examples ready to share.
✨Demonstrate Collaboration Skills
This role involves partnering closely with data scientists and engineers, so be ready to discuss how you've collaborated in the past. Share specific instances where your teamwork helped keep AI systems stable and fast, as this will show you're a great fit for their culture.