MLOps Engineer — AWS SageMaker

4 hours ago

india, IN Hadron Talent -Hadronfinsys Full time

Role Overview

We are seeking a SageMaker MLOps Developer to design and implement machine learning operations workflows on AWS SageMaker. This role focuses on automating ML pipelines, managing model lifecycle, and ensuring scalable, secure deployments in production environments.


Key Responsibilities

  • Develop MLOps Pipelines
  • Build and automate ML workflows using AWS SageMaker, SageMaker Pipelines, and Step Functions for training, deployment, and monitoring.
  • Model Lifecycle Management
  • Manage models through development, staging, and production using SageMaker Model Registry.
  • CI/CD Integration
  • Implement CI/CD pipelines for ML projects using AWS CodePipeline, CodeBuild, and Git-based workflows.
  • Data Preparation & Feature Engineering
  • Collaborate with data engineers and scientists to prepare datasets and optimize feature pipelines on AWS.
  • Monitoring & Governance
  • Set up monitoring for model performance, data drift, and compliance using Amazon CloudWatch, SageMaker Model Monitor, and AWS Config.
  • Security & Compliance
  • Ensure proper IAM roles, encryption, and governance for ML workflows.


Required Skills & Qualifications

  • Hands-on experience with AWS SageMaker, SageMaker Pipelines, and Model Registry.
  • Strong programming skills in Python and SQL.
  • Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
  • Experience with AWS services (S3, Lambda, CloudWatch, IAM).
  • Knowledge of CI/CD tools (AWS CodePipeline, Jenkins, GitHub Actions).
  • Understanding of containerization (Docker) and orchestration (ECS/EKS).


Preferred Qualifications

  • AWS Certified Machine Learning – Specialty or Solutions Architect.
  • Experience with feature store concepts and ML observability tools.
  • Exposure to Kubeflow or other ML orchestration frameworks.


Soft Skills

  • Strong problem-solving and analytical skills.
  • Excellent communication and teamwork abilities.

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