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Tier-1 brand, mid-level DevOps title, metro location, and broad popular skillset create high competition.
Specialized MLOps, Azure and Kubernetes requirements limit cross-industry transferability, increasing sensitivity.
Explicit years plus mandatory Azure, Kubernetes, CI/CD and MLOps skills make shortlisting highly strict.
Design, implement, and maintain CI/CD deployment pipelines for batch and real-time ML models on on-premise and Azure cloud environments.
Ensure security, compliance, observability (logging, monitoring, alerting), and optimize deployments for performance, scalability, and reliability.
Deploy and manage containerized workloads using Docker and Kubernetes; independently lead design, solutioning, and estimations while collaborating across business and technical teams.
5-8+ years of relevant experience in DevOps/MLOps or related roles.
Bachelor's degree in Computer Science, Information Technology or equivalent.
Technical proficiency with Azure DevOps, Azure cloud services (Synapse, Databricks, Azure Apps, AKS), containerization (Docker, Kubernetes), big data frameworks (Apache Spark, Hadoop), scripting (Python, Shell), and ML model serving/monitoring frameworks.
Location: Pune, Maharashtra; Work Arrangement: Hybrid; Full-Time position.
Experienced in independently owning end-to-end deployment pipelines for ML and data analytics solutions in hybrid cloud setups.
Skilled in embedding security best practices ensuring governance and regulatory compliance in deployments.
Collaborative operator comfortable engaging with cross-functional teams including Data Science, Data Architecture, DevOps, and Business stakeholders to drive MLOps best practices.