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- Tasks: Deploy and scale ML models, build reliable pipelines, and collaborate with top tech teams.
- Company: Leading global healthcare provider transforming health outcomes with AI-driven solutions.
- Benefits: Competitive daily rate, contract flexibility, and the chance to work on impactful projects.
- Other info: Dynamic, collaborative environment with opportunities for professional growth.
- Why this job: Join a cutting-edge team at the forefront of AI and healthcare innovation.
- Qualifications: 5+ years in ML Ops, strong Azure experience, and problem-solving skills.
The predicted salary is between 130000 - 143000 £ per year.
Contract Length: 4/6 Months
Start Date: ASAP
Rate: 500/550 GBP per day (Inside ir35)
Must be UK based
We’re currently supporting a leading global healthcare provider that is transforming health outcomes through insurance, clinical services, and AI-driven care solutions. They’re looking for a Senior ML Ops Engineer to help build and scale production-grade machine learning infrastructure within a modern cloud-native environment. This is a high-impact opportunity to work at the intersection of AI, platform engineering, and cloud infrastructure for one of the most innovative organisations in the healthcare space.
What you’ll be doing:
- Deploying and scaling ML models in production
- Building reliable ML pipelines and deployment systems
- Working across Azure cloud, ML Studio, and Kubernetes environments
- Implementing model versioning, monitoring, observability, and governance
- Improving inference performance, resilience, and platform uptime
- Collaborating closely with Data Scientists, DevOps, and Engineering teams
Tech Stack:
- Python
- Azure
- Azure ML Studio
- ML Pipelines
- Docker
- Kubernetes
- GitHub Actions
- SQL
What they’re looking for:
- 5+ years of ML Ops experience
- Strong experience supporting production ML systems at scale
- Deep understanding of Azure cloud infrastructure
- Experience with monitoring/observability tooling (Prometheus, Grafana, Datadog, OpenTelemetry)
- Strong problem-solving and debugging skills
This is a fantastic opportunity for someone passionate about building scalable AI infrastructure and operationalising machine learning in a fast-moving, collaborative environment.
ML Ops Engineer in Edinburgh employer: Talent Connect Group (TCG)
Contact Detail:
Talent Connect Group (TCG) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Ops Engineer in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work in healthcare tech or ML Ops. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Azure, Kubernetes, and ML pipelines. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common ML Ops scenarios. Think about how you would tackle challenges like model versioning or improving inference performance. We want you to shine when it comes to problem-solving!
✨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 love seeing candidates who are proactive about their job search.
We think you need these skills to ace ML Ops Engineer in Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the ML Ops Engineer role. Highlight your experience with Azure, Kubernetes, and any relevant projects that showcase your skills in deploying ML models and building pipelines.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about ML Ops and how your background aligns with the healthcare sector. Don’t forget to mention specific tools and technologies you’ve worked with.
Showcase Your Problem-Solving Skills: In your application, include examples of how you've tackled challenges in previous roles. This could be anything from improving model performance to debugging complex systems. We love seeing how you think!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be one step closer to joining our innovative team at StudySmarter!
How to prepare for a job interview at Talent Connect Group (TCG)
✨Know Your Tech Stack
Make sure you’re well-versed in the tech stack mentioned in the job description. Brush up on your Python, Azure, and Kubernetes skills, and be ready to discuss how you've used these technologies in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex issues in ML Ops. Think about specific challenges you've faced with model deployment or scaling and how you resolved them. This will demonstrate your strong problem-solving abilities.
✨Understand the Company’s Mission
Research the healthcare provider's goals and how they leverage AI to improve health outcomes. Being able to articulate how your role as an ML Ops Engineer fits into their mission can set you apart from other candidates.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with Data Scientists and DevOps teams, be ready to discuss your experience in collaborative environments. Share examples of successful teamwork and how you’ve contributed to cross-functional projects.