MLOps Engineer

Key Skills

• Hands-on experience with Amazon SageMaker
• CI/CD setup for ML models using AWS CodePipeline & CodeBuild
• Strong experience with Docker and container orchestration (ECS/Fargate)
• ML model deployment, monitoring, and lifecycle management
• Data pipeline development using Python, PySpark, and Snowflake
• Proficiency in SQL and Bash/Shell scripting
• Experience with ML libraries: Pandas, NumPy, PyTorch, Scikit-learn
• Strong knowledge of AWS services: S3, IAM, Lambda, Step Functions, ECR
• Data and model quality monitoring experience

Key Responsibilities

• Build and automate end-to-end ML pipelines
• Deploy and manage ML models in production
• Monitor model performance and data quality
• Maintain CI/CD workflows and infrastructure
• Ensure security, compliance, and system reliability
• Continuously optimize performance and cost

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