Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Deploy and scale ML models, build reliable pipelines, and collaborate with top teams.
- Company: Leading global healthcare provider transforming health outcomes with AI-driven solutions.
- Benefits: Competitive daily rate, contract flexibility, and impactful work in a modern environment.
- Other info: Dynamic, collaborative environment with opportunities to innovate and grow.
- Why this job: Join a high-impact role at the forefront of AI and cloud infrastructure in healthcare.
- Qualifications: 5+ years in ML Ops, strong Azure experience, and problem-solving skills.
The predicted salary is between 50000 - 66000 £ 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 Chesterfield 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 Chesterfield
✨Tip Number 1
Network like a pro! Reach out to your connections in the ML Ops space, especially those who work in healthcare. 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 ML projects, especially those involving Azure and Kubernetes. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common ML Ops scenarios. Be ready to discuss how you've tackled challenges in deploying models or improving system performance. Real-world examples will make you shine!
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities waiting for talented folks like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace ML Ops Engineer in Chesterfield
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with ML Ops and the specific technologies mentioned in the job description. We want to see how your skills align with what we're looking for, so don’t be shy about showcasing your relevant projects!
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 you can contribute to our mission in healthcare. We love seeing enthusiasm and a personal touch, so let your personality come through.
Showcase Your Problem-Solving Skills: In your application, highlight specific examples where you've tackled challenges in ML systems or cloud infrastructure. We’re keen on seeing how you approach problems and what solutions you've implemented in past roles.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications better and ensures you get all the updates regarding your application status. Plus, it’s super easy!
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 ML Ops Experience
Prepare specific examples of your experience with deploying and scaling ML models. Be ready to talk about the challenges you faced and how you overcame them, especially in production environments.
✨Understand the Company’s Mission
Research the healthcare provider's mission and values. Understanding their focus on transforming health outcomes through AI-driven solutions will help you align your answers with their goals during the interview.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the tools they use for monitoring and observability, and how they measure success in ML Ops. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.