GG10.2 Role Value Proposition MLOps Engineer plays a critical role in the Data & Analytics life cycle. The role requires one to demonstrate expertise in CI/CD automation, cloud platforms, containerization, and operational monitoring. It is an individual contributor role, expected to independently function Experience 5-8+ years of relevant experience Education Bachelors degree in computer science, information technology or equivalent educational qualification Responsibilities
- Design, implement, and maintain deployment pipelines for batch and real-time models using on-prem and Azure cloud
- Embed security best practices in deployments to ensure compliance with enterprise, governance, and regulatory standards.
- Implement observability frameworks (logging, monitoring, alerting) to ensure reliability and performance.
- Optimize deployments for performance, scalability and reliablity
- Manage infrastructure for data pipelines and ML workloads across on-premise and cloud environments.
- Deploy and manage containerized workloads using Docker and Kubernetes.
- Drive adoption of best practices in DevOps and MLOps across the Data & Analytics ecosystem.
- Document pipelines, environments,
and operational standards for cross-team use.Design, implement, and maintain CI/CD pipelines for data, analytics, and ML solutions.
- Independently lead design, solutioning & estimations
- Collaborate with multiple partners from Business, Technology, Operations and D&A; capabilities (Data Governance, Data Quality, Data Modeling, Data Architecture, Data science, DevOps, BI & insights) Technical Skills
- Deployment tools (Azure DevOps, Tosca,YAML Scripting, code versioning tools)
- Big Data Frameworks : Apache Spark, Hadoop
- Azure cloud services ( Synapse, Databricks, Azure Apps, AKS)
- Containerization and orchestration (Docker, Kubernetes, )
- Protocols/technologies like HTTP, SSL, LDAP, JDBC, SQL, XML
- Python, ML model serving and monitoring frameworks (MLflow, Azure ML)
- Shell Scripting : Powershell, bash, CMD, CLI
- Rest APIs, Postman
- Communication skills, analytical skills, structured problem-solving skills
- Partner, Stakeholder engagement experience
Valuable To have
- DevOps certification
- Infrastructure acess managment( RBAC, Keyvault, CyberArk)
- Exposure to Gen AI technology and tools
📌 DevOps Engineer II (Pune)
🏢 MetLife
📍 Pune