Queen Square Recruitment
Azure MLOps Engineer
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Azure MLOps Engineer
📍 Reading (Office-Based)
📅 6-Month Initial Contract
⏰ ASAP Start
💷 £450 - £500 per day (Inside IR35)
We are seeking an experienced Azure MLOps Engineer with a strong passion for automation, scalability, and cloud engineering to join a rapidly growing team based in Reading. This is an exciting opportunity to play a key role in building and maintaining enterprise-scale machine learning platforms, supporting data processing at terabyte scale and enabling innovative analytical and forecasting solutions.
Working closely with Architects, Data Scientists, Forecasters, Developers, and DevOps specialists, you will help deliver secure, reliable, and highly automated Azure-based MLOps infrastructure.
Key Responsibilities
- Deploy machine learning models into production environments in collaboration with Data Scientists and Forecasters.
- Implement and maintain scalable, secure, and highly available Azure MLOps infrastructure.
- Follow established deployment strategies to ensure safe and controlled production releases.
- Design and manage Azure cloud resources required for model hosting and inference.
- Utilise Docker and containerisation technologies to package models and dependencies.
- Establish monitoring, logging, and alerting solutions to track model health, performance, and reliability.
- Continuously monitor, maintain, and optimise production ML models.
- Improve scalability and cost efficiency across cloud infrastructure and ML workloads.
- Implement auto-scaling capabilities and parallel processing mechanisms to support fluctuating demand.
- Ensure security best practices and compliance with data governance and regulatory requirements.
- Manage data pipelines and storage solutions supporting model training and inference workloads.
- Implement data versioning and lineage tracking to ensure data integrity and traceability.
- Work collaboratively with engineering, DevOps, and business stakeholders to deliver robust ML solutions.
- Identify system bottlenecks and drive continual performance improvements.
- Produce and maintain clear technical documentation covering deployments, configurations, and architecture.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Essential Experience
- 5+ years' experience in MLOps, DevOps, Machine Learning Engineering, or a related field.
- Strong understanding of machine learning concepts and model lifecycle management.
- Demonstrable experience building and automating cloud-based ML platforms.
- Deep understanding of software engineering principles and ML model deployment.
- Extensive experience with Azure Machine Learning and Azure cloud services.
- Strong Python development skills.
- Experience working with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Hands-on experience creating CI/CD pipelines and release processes using Azure DevOps.
- Experience supporting real-time inference and production ML environments.
- Strong knowledge of monitoring and observability practices for ML workloads.
- Experience with SQL and NoSQL databases.
- Strong knowledge of Azure SQL Database and Azure Storage Accounts, including Blob Storage.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Desirable Skills
- Experience with MLOps frameworks and tooling.
- Familiarity with data engineering concepts and modern data platforms.
- Knowledge of tools, methodologies, and frameworks used by Data Scientists.
- Experience working with data formats including Parquet, JSON, GRIB, and NetCDF.
- Azure Data Scientist Associate certification.
- Experience optimising large-scale ML workloads in Azure environments.
If you're an experienced Azure MLOps Engineer available for an immediate start and looking for your next contract opportunity, we'd love to hear from you. Apply now to discuss the opportunity further.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location