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
7. LLMOps implementation experience
📌 Opening For Mlops For Pan india (Bengaluru)
🏢 Capgemini
📍 Bengaluru
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