Job Responsibilities: Own and drive the enterprise MLOps and data platform architecture, leading development of enterprise-wide MLOps and Generative AI frameworks. Lead DevOps practices and CI/CD implementation for ML and data platforms, ensuring reliable and automated deployments. Key Competencies: Strong system design and architecture mindset, ability to build platforms, not just pipelines.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, or related field
  • 6+ years of experience in MLOps, DevOps, Platform Engineering, or Data Engineering
  • Strong experience building and operating enterprise-scale ML platforms
  • Hands-on experience with AWS (preferred) or other cloud platforms
  • Strong experience with CI/CD tools (Jenkins, GitHub Actions, etc.)
  • Experience with Infrastructure as Code (Terraform, Terragrunt, CloudFormation)
  • Experience with containerization and orchestration (Docker, Kubernetes)
  • Strong understanding of ML lifecycle management and MLOps tools (MLflow, SageMaker, Databricks, etc.)
  • Experience with data engineering systems (ETL/ELT pipelines, feature stores, large-scale data processing)
  • Experience implementing observability and monitoring frameworks
  • Strong understanding of security and governance in cloud and ML systems