Senior ML Engineer — Production ML & MLOps

Stott and May; Brussel; Sur place; EUR 60 000 - 100 000; Plein temps

Résumé du poste

Stott and May is seeking an experienced Machine Learning Engineer to join a large-scale AI and data transformation programme. You will design, deploy and optimise production-grade ML solutions within a modern cloud and data environment.

Working alongside Data Scientists, Data Engineers and IT teams, you will take machine learning models from concept through to production, ensuring they are scalable, automated and fully monitored throughout their lifecycle.

Qualifications

• Minimum 4 years' commercial experience as a Machine Learning Engineer or MLOps Engineer.

Responsabilités

• 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.

Connaissances

Python

CI/CD

Agile

Distributed systems

Model optimization

Data visualization

Outils

Docker

Kubernetes

GitLab CI

PostgreSQL

Description du poste

Stott and May is seeking an experienced Machine Learning Engineer to join a large-scale AI and data transformation programme. You will design, deploy and optimise production-grade ML solutions within a modern cloud and data environment.

Working alongside Data Scientists, Data Engineers and IT teams, you will take machine learning models from concept through to production, ensuring they are scalable, automated and fully monitored throughout their lifecycle.