Capgemini looking For Mlops Engineer

Role & responsibilities

MLOps Engineer having experience in design and implementation of scalable, secure, and production-grade ML platforms across multi-cloud environments (Azure, AWS, GCP).

The role involves architecting end-to-end ML lifecycle solutions, enabling reproducibility, governance, and operational excellence while working closely with data science, platform engineering, and cloud teams.

Preferred candidate profile

1. overall experience and dedicated MLOps / AI Platform Engineering experience
2. Kubernetes hands-on expertise
3. Python development experience
4. CI/CD implementation experience
5. Monitoring and observability experience
6. LLMOps implementation experience

LLMOps implementation experience