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For Companies At a Glance
- Tasks: Build and scale AI infrastructure while collaborating with data science and engineering teams.
- Company: Dynamic tech company in Edinburgh and London, focused on AI innovation.
- Benefits: Competitive pay, hands-on experience, and potential for contract extension.
- Why this job: Join a cutting-edge team and work on impactful AI projects.
- Qualifications: Experience in AI Ops, MLOps, or Infrastructure Engineering; scripting skills required.
- Other info: Onsite work 3 days a week with opportunities for growth.
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 England 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 England
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and MLOps community on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI infrastructure or MLOps. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Linux, automation, and distributed systems. We want to see how you can contribute to building and operating production AI environments!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Infrastructure / MLOps Engineer (Contract) in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI Ops, MLOps, and Infrastructure Engineering. We want to see how your skills align with the role, 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 engaging and personal – we love to see your personality come through!
Showcase Your Technical Skills: When filling out your application, make sure to mention your hands-on experience with Linux, automation, and scripting. If you've worked with GPU-based systems or CI/CD pipelines, let us know! We’re keen to see what you bring to the table.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our awesome team at StudySmarter!
How to prepare for a job interview at WorkGenius Group
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of AI infrastructure and MLOps. Be ready to discuss your hands-on experience with Linux, automation, and scripting in Python or Bash. They’ll likely ask you about specific projects you've worked on, so have a couple of examples ready that showcase your skills.
✨Showcase Your Collaboration Skills
This role involves working closely with data scientists and engineers, so be prepared to talk about how you’ve successfully collaborated in the past. Think of examples where you’ve partnered with others to solve problems or improve processes, especially in high-pressure environments.
✨Demonstrate Your Automation Know-How
Since automating workflows is key for this position, be ready to discuss your experience with CI/CD pipelines and any tools you’ve used for automation. If you can, share specific instances where your automation efforts led to improved efficiency or stability in ML production environments.
✨Familiarise Yourself with Their Tools
If you know they use specific monitoring and observability tools like Prometheus or Grafana, do a bit of research on them. Even if you haven’t used these exact tools, understanding their purpose and functionality will show that you’re proactive and eager to learn.
