Architect Machine Learning (MLOps Specialist) (Mumbai)

Architect and implement the MLOps strategy for the EVOKE Phase-2 programme, ensuring alignment with the project proposal and delivery roadmap. Design and own enterprise-grade ML/LLM pipelines covering model training, validation, deployment, versioning, monitoring, and CI/CD automation. Build container-oriented ML platforms (EKS-first) while evaluating alternative orchestration tools with similar capabilities (Kubeflow, SageMaker, MLflow, Airflow, etc.). Implement hybrid MLOps + LLMOps workflows, including prompt/version governance, evaluation frameworks, and monitoring for LLM-based systems. Serve as a technical authority across multiple internal and customer projects, not limited to EVOKE, contributing architectural patterns, best practices, and reusable frameworks. Enable observability, monitoring, drift detection, lineage tracking, and auditability across ML/LLM systems. Collaborate with cross-functional teams data engineering, platform, DevOps, and client stakeholders to deliver production-ready ML solutions. Ensure all solutions adhere to security, governance, and compliance expectations, particularly around handling cloud services, Kubernetes workloads, and MLOps tools. Conduct architecture reviews, troubleshoot complex ML system issues, and guide teams through implementation across cloud-native ML platforms. Mentor engineers and provide guidance on modern MLOps tools, platform capabilities, and best practices. If you like .