Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and scale AI infrastructure while collaborating with data science and engineering teams.
- Company: Dynamic tech company focused on innovative AI solutions.
- Benefits: Competitive pay, flexible contract duration, and potential for extension.
- Why this job: Join a cutting-edge team and make an impact in the AI landscape.
- Qualifications: Experience in AI Ops, MLOps, or Infrastructure Engineering is essential.
- Other info: Onsite work in Edinburgh 3 days a week with great career growth potential.
The predicted salary is between 48000 - 72000 £ per year.
Location: Edinburgh, UK and/or London, UK
Onsite: 3 days per week (mandatory)
Start: ASAP
Duration: 12–24 months (high likelihood of extension)
About the Role
This role focuses on building, operating, and scaling AI infrastructure, ensuring stable, performant, and automated ML production environments in close collaboration with data science and engineering teams.
What You’ll Do
- Build and operate production AI / ML infrastructure
- Support model deployment, monitoring, scaling, and lifecycle management
- Automate workflows for training, evaluation, and deployment pipelines
- Work with GPU-based systems, distributed compute, and CI/CD pipelines
- Partner closely with data scientists and engineers to keep AI systems stable, efficient, and scalable
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 and orchestration (Docker, Kubernetes, or similar)
- Comfortable working onsite in Edinburgh 3 days/week
Nice to Have
- GPU / CUDA experience
- Exposure to HPC or large-scale AI platforms
- Experience with monitoring & observability tools (e.g., Prometheus, Grafana)
AI Infrastructure / MLOps Engineer (Contract) in Slough employer: WorkGenius Group
Contact Detail:
WorkGenius Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Infrastructure / MLOps Engineer (Contract) in Slough
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and MLOps 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 role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to AI infrastructure or MLOps. We love seeing real-world applications of your expertise, so don’t hold back on sharing your successes!
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with tools like Docker, Kubernetes, and CI/CD pipelines. We want to see how you can contribute to our team right from the get-go.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. We’re excited to find someone who’s as passionate about AI infrastructure as we are, so don’t hesitate to hit that apply button!
We think you need these skills to ace AI Infrastructure / MLOps Engineer (Contract) in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Infrastructure / MLOps Engineer role. Highlight your experience with Linux, automation, and any relevant projects you've worked on. We want to see how your skills align with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI Ops and MLOps. Share specific examples of how you’ve built or operated production AI infrastructure in the past. Let us know why you’d be a great fit for our team!
Showcase Your Technical Skills: Don’t forget to showcase your technical skills in your application. Mention your hands-on experience with distributed systems, containers, and CI/CD pipelines. We love seeing candidates who are comfortable with GPU-based systems and automation tools!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at WorkGenius Group
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description. Brush up on your Linux skills, scripting in Python or Bash, and get comfortable discussing distributed systems and CI/CD pipelines. Being able to talk confidently about your hands-on experience will impress the interviewers.
✨Showcase Your Collaboration Skills
This role requires close collaboration with data scientists and engineers, so be prepared to discuss past experiences where you’ve worked in a team. Highlight how you’ve contributed to keeping AI systems stable and efficient, and share specific examples of successful partnerships in your previous roles.
✨Prepare for Technical Questions
Expect technical questions that dive deep into AI infrastructure and MLOps. Review common challenges faced in model deployment and lifecycle management. Practising problem-solving scenarios related to automation workflows and GPU-based systems can give you an edge during the interview.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the current AI infrastructure challenges they face or how they measure the success of their ML production environments. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.
