Machine Learning Engineer
Role details
Job location
Tech stack
Job description
The Machine Learning Engineer plays a key role in enabling the industrialization of Machine Learning and AI solutions within the enterprise. The mission of the role is to promote and apply best practices in production-ready ML development, ensuring that AI solutions are robust, scalable, monitored, and fully integrated into IT production environments.
Machine Learning Engineers bridge the gap between AI & Analytics teams and IT production, ensuring that Machine Learning models deployed to production are supported by appropriate data pipelines, infrastructure, automation, and monitoring from both a technical and business perspective.
They contribute to the full lifecycle of AI services, from design and development to deployment, monitoring, and continuous improvement.
Requirements
Minimum 4 years of relevant experience as a Machine Learning Engineer, ML Platform Engineer, or similar role
Technical Skills
- Strong experience with containerization and virtualization (Docker, VMs)
- Experience with AI platforms and development environments
- CI/CD pipelines, preferably GitLab CI
- Code, data, and model versioning practices
- Advanced Python development
- Package management and dependency management
- PostgreSQL
Preferred
- Experience integrating systems across different technologies (distributed systems, mainframe environments)
- Model optimization and compression techniques
- ELT / ETL tools
- Big data technologies (e.g. Apache Spark)
- Data flow processing frameworks
- Data visualization tools
About the company
Capgemini ist einer der weltweit führenden Anbieter von Management- und IT-Beratung, Technologie-Services und Digitaler Transformation. Als ein Wegbereiter für Innovation unterstützt das Unternehmen seine Kunden bei deren komplexen Herausforderungen rund um Cloud, Digital und Plattformen.
