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# Machine Learning Engineer

- **Company:** Stott and May
- **Location:** Brussel, Belgium (Remote available)
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Agile Methodology, Artificial Intelligence, Big Data, Software Quality, Extract Transform Load (ETL), Data Transformation, Distributed Systems, PostgreSQL, Machine Learning, Azure Machine Learning, Data Streaming, Management of Software Versions, Apache Spark, Build Management, AI Platforms, Gitlab-ci, Kubernetes, Machine Learning Operations, Software Version Control, Data Pipelines, Docker
- **Published:** July 29, 2026
- **Apply:** https://find.stottandmay.com/job/senior-machine-learning-engineer-78637/apply

## About the Role

* Minimum 4 years' commercial experience as a Machine Learning Engineer or MLOps Engineer.
 * Advanced Python development skills.
 * Strong experience with containerisation technologies (Docker/Kubernetes or similar).
 * Experience building and maintaining CI/CD pipelines (GitLab CI or equivalent).
 * Experience with model, code and data versioning.
 * Strong knowledge of package and dependency management.
 * Experience working with PostgreSQL.
 * Strong understanding of Agile delivery methodologies.

Desirable Experience

 * Apache Spark or other big data technologies.
 * ETL/ELT pipeline development.
 * Data flow processing.
 * Integration across distributed systems and enterprise platforms.
 * Model optimisation and compression techniques.
 * Data visualisation tools.
 * Experience deploying AI solutions into enterprise production environments.

## Description

Working alongside Data Scientists, Data Engineers and IT teams, you will play a key role in taking machine learning models from concept through to production, ensuring they are scalable, automated and fully monitored throughout their lifecycle., * Design, build and deploy production-ready machine learning pipelines.

 * Work closely with Data Scientists to develop scalable ML solutions that meet business and technical requirements.
 * Build and maintain CI/CD pipelines for machine learning deployments.
 * Develop and manage containerised ML applications using modern virtualisation technologies.
 * Implement robust model monitoring, retraining and performance optimisation processes.
 * Design and maintain data pipelines to support AI services and model deployment.
 * Ensure high standards of code quality, version control and dependency management.
 * Support production environments by troubleshooting, monitoring and improving deployed ML services.
 * Collaborate with cross-functional teams including Data Science, Engineering, Infrastructure and Operations.
 * Drive best practices across MLOps, automation and industrialised machine learning delivery.


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