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
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