At a Glance
- Tasks: Deploy and maintain scalable machine learning solutions on Microsoft Azure.
- Company: Join a dynamic team in a growing tech environment.
- Benefits: Competitive daily rate, hands-on experience, and collaborative culture.
- Other info: Office-based role with excellent opportunities for professional growth.
- Why this job: Make an impact by optimising ML platforms and working with cutting-edge technology.
- Qualifications: 5+ years in MLOps or DevOps, strong Azure and Python skills required.
The predicted salary is between 63000 - 77000 £ per year.
We are looking for an experienced Azure MLOps Engineer to join a growing team responsible for building, deploying, and maintaining scalable machine learning solutions on Microsoft Azure. You will work closely with Data Scientists, DevOps Engineers, Architects, and Software Developers to deliver reliable, secure, and automated MLOps platforms supporting large-scale data processing and production ML workloads.
Key Responsibilities
- Deploy machine learning models into Azure production environments.
- Design, implement, and maintain Azure MLOps infrastructure.
- Build and manage CI/CD pipelines for machine learning solutions using Azure DevOps.
- Containerize applications and ML models using Docker.
- Monitor model performance, health, and reliability in production.
- Implement logging, monitoring, and alerting solutions.
- Optimize infrastructure for scalability, performance, and cost efficiency.
- Implement automated deployment and scaling strategies.
- Manage Azure cloud resources supporting ML workloads.
- Ensure security, governance, and compliance with data protection standards.
- Manage data pipelines, storage, versioning, and lineage.
- Collaborate with cross-functional teams to support end-to-end ML life cycle management.
- Troubleshoot production issues and continuously improve platform performance.
- Maintain technical documentation and communicate effectively with both technical and non-technical stakeholders.
Required Skills & Experience
- 5+ years' experience in MLOps, DevOps, or a related field.
- Strong experience with Azure Machine Learning.
- Hands-on experience with Azure DevOps CI/CD pipelines.
- Strong Python programming skills.
- Experience with Docker and containerized deployments.
- Good understanding of the machine learning life cycle and production deployment.
- Experience with Azure SQL Database, Azure Storage (Blob Storage), and SQL/NoSQL databases.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Experience monitoring and supporting production ML models.
- Knowledge of infrastructure automation and scalable cloud architectures.
- Experience supporting Real Time inference using Azure Machine Learning.
Desirable Skills
- Azure Data Scientist Associate certification.
- Experience with data engineering tools and practices.
- Familiarity with GRIB, NetCDF, Parquet, and JSON data formats.
- Experience working with enterprise MLOps frameworks.
Azure MLOps Engineer - Inside IR35 - Onsite in Wokingham employer: Hamilton Barnes
Hamilton Barnes is an exceptional employer, offering a dynamic work environment in London where innovation meets opportunity. With competitive salaries, night shift allowances, and a strong focus on employee development through ongoing training, we empower our Field Service Engineers to advance their careers while enjoying a supportive team culture. Join us to be part of a growing engineering team that values your skills and fosters professional growth.
