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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 opportunity, and impactful work in healthcare innovation.
- Other info: Fast-paced environment with opportunities for professional growth and collaboration.
- Why this job: Join a dynamic team at the forefront of AI and cloud infrastructure in healthcare.
- Qualifications: 5+ years of ML Ops experience and strong Azure cloud skills required.
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 Woking 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 Woking
✨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 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 deployed models in production and tackled challenges with monitoring and observability tools. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace ML Ops Engineer in Woking
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 candidates who can demonstrate their problem-solving abilities, especially in high-pressure environments.
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 don’t miss out on any important updates from us!
How to prepare for a job interview at Talent Connect Group (TCG)
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Azure, Kubernetes, and Python. Brush up on your experience with ML pipelines and deployment systems, as you’ll likely be asked to discuss how you’ve used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in ML Ops and how you resolved them. Highlight your debugging skills and any monitoring tools you've used, such as Prometheus or Grafana, to demonstrate your hands-on experience.
✨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 will show your genuine interest and alignment with their values.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with Data Scientists and DevOps teams, think of examples where you successfully collaborated across disciplines. Be ready to discuss how you communicate technical concepts to non-technical team members, as this is crucial in a collaborative environment.