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- 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 shape the future of healthcare.
- Why this job: Join a high-impact role at the forefront of AI and healthcare innovation.
- Qualifications: 5+ years in ML Ops, strong Azure experience, and problem-solving skills.
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.
If interested, or if you know someone suitable, feel free to message me directly or email liam.moir-holland@tconnectgroup.com
ML Ops Engineer 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
✨Tip Number 1
Network like a pro! Reach out to your connections in the ML Ops space, especially those who work with Azure and Kubernetes. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous ML Ops projects, especially those involving production-grade systems. 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 your problem-solving skills. Be ready to discuss how you've tackled challenges in deploying ML models and improving system performance. Real-world examples will make you stand out!
✨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’re always looking for passionate individuals like you to join our team!
We think you need these skills to ace ML Ops Engineer
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 and scaling ML models.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about building scalable AI infrastructure and how your background aligns with the needs of the healthcare provider.
Showcase Your Tech Stack Knowledge: Don’t forget to mention your familiarity with the tech stack listed in the job description. Whether it's Python, Docker, or monitoring tools like Prometheus, make sure we see your expertise!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any updates!
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, Kubernetes, and any monitoring tools like Prometheus or Grafana. Being able to discuss your hands-on experience with these technologies will show that you’re ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in ML Ops and how you tackled them. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will demonstrate your strong problem-solving abilities and give the interviewers confidence in your skills.
✨Understand the Company’s Mission
Research the healthcare provider's mission and how they leverage AI to transform health outcomes. Be ready to discuss how your role as a Senior ML Ops Engineer can contribute to their goals. Showing genuine interest in their work will set you apart from other candidates.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with Data Scientists, DevOps, and Engineering teams, think of examples where you’ve successfully collaborated in the past. Highlight your communication skills and ability to work in a team, as this is crucial in a fast-moving environment.