MetLife

Position Summary

 MetLife established a Global capability center (MGCC) in India to scale and mature Data & Analytics, technology and operations capabilities in a cost-effective manner and make MetLife future ready. The center is integral to Global Technology and Operations with a focus to protect & build MetLife IP, promote reusability and drive experimentation and innovation. The Data & Analytics team in India mirrors the Global D&A team with an objective to drive business value through trusted data, scaled capabilities, and actionable insights. The operating models consists of business aligned data officers- US, Japan and LatAm & Corporate functions enabled by enterprise COEs- data engineering, data governance and data science

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

Job 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) 

Knowledge, Skills and Abilities

Education

Bachelor’s degree in computer science, information technology or equivalent educational qualification

Technical Skills and Experience

• 5-8+ years of relevant experience
 

 •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
  

Good to Have (Preferred)

•DevOps certification
 •Infrastructure access management ( RBAC, Keyvault, CyberArk)
 • Exposure to Gen AI technology and tools