Maidenhead, United Kingdom | Posted on 20/04/2026
VE3 is a technology and business consultancy focused on delivering end-to-end technology solutions and products. We have successfully serviced enterprises across multiple markets, including the public and private sectors. Our services span all aspects of business, providing a holistic approach to managing an organization. We are committed to providing technical innovations and tools that empower organizations with critical information to facilitate decision-making that results in business transformation through cost savings and increased operational efficiency. Our commitment to quality is adopted throughout the organization and sets the foundation for delivering our full suite of capabilities.
Job Description
Role Summary The ML / MLOps Engineer is responsible for industrialising machine learning solutions by establishing reliable deployment, monitoring, retraining, and lifecycle management practices. The role bridges data science and production engineering, ensuring that models are secure, scalable, observable, and supportable in live environments.
Requirements
Key Responsibilities
* Package, deploy, and manage ML models across development, test, and production environments.
* Build and maintain MLOps pipelines for training, validation, release, monitoring, and retraining.
* Implement model versioning, performance tracking, drift monitoring, and rollback mechanisms.
* Support CI/CD and automation for ML workloads and associated infrastructure.
* Collaborate with data scientists and engineers to productionise analytical assets.
* Ensure secure, scalable, and resilient operation of model services.
* Support logging, observability, alerting, and operational troubleshooting.
* Produce technical documentation and support knowledge transfer to delivery and support teams.
Experience
* Proven experience deploying and operating ML models in production.
* Strong experience with MLOps practices, CI/CD, automation, and cloud-native deployment.
* Experience with model monitoring, lifecycle management, and performance optimisation.
* Experience working with data science teams to productionise experiments and models.
* Strong scripting and engineering capability.
Skills
* MLOps and ML lifecycle management
* CI/CD and automation
* Model deployment and monitoring
* Python and scripting
* Observability and operational support
Qualifications / Certifications
* Degree in computer science, software engineering, data science, or related field
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