Jobs → Data & Analytics → Software Engineer – Machine Learning (AWS MLOps & Data Platform)

About the Role We are looking for a Software Engineer with expertise in Machine Learning, AWS MLOps, and Data Platform to build, automate, and scale production-grade ML pipelines and Lakehouse architectures on AWS. Key Responsibilities • AWS MLOps & Production Engineering • SageMaker Pipeline Management: Hands-on model deployment, monitoring, versioning, and lifecycle management. • AWS Stack: Deep expertise in SageMaker, ECS/EKS, Lambda, Step Functions, S3, IAM, CloudWatch, VPC. • IaC & CI/CD: Strong experience building Infrastructure as Code using AWS CDK / CloudFormation (or Terraform) and CI/CD pipelines. • Containers: Experience with Docker, Kubernetes (EKS). • Data Engineering & Lakehouse Architecture • Data Lakehouse: Building data lakes using AWS Glue, Lake Formation, Athena, Data Catalog, and Apache Iceberg. • ETL/ELT & Data Quality: Building robust data ingestion frameworks, data lineage, and governance. • Core Tech: Strong Object-Oriented Python (SOLID principles, DRY design), Advanced SQL, and exposure to PyTorch / TensorFlow / Scikit-Learn. Requirements • 5+ Years in Software Engineering with a strong focus on AWS MLOps + Data Engineering. • Proven track record of putting ML models into production (not just Jupyter notebook experiments). • Hands-on experience with AWS CDK and Apache Iceberg / Lake Formation.