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Machine learning ops

October 23, 2026

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Job Description & Key Requirements<ul><li>Role: MLOps Specialist / Senior MLOps Engineer</li><li>Work Mode: Hybrid</li><li>Experience: 5+ Years in DevOps / Cloud / MLOps</li></ul>Core Technical Stack & Responsibilities:<ul><li>ML Lifecycle & Platforms: End-to-end training and inference pipelines, model deployment, monitoring (data/concept drift detection), automated retraining, and Feature Store management using AWS SageMaker, MLflow, Kubeflow, or Databricks.</li><li>Cloud & Infrastructure: Hands-on AWS infrastructure automation (SageMaker, Lambda, S3, ECS, IAM, RDS) and container orchestration using Docker, Kubernetes / EKS.</li><li>Infrastructure as Code (IaC): Solid hands-on provisioning using Terraform and CloudFormation (CFT).</li><li>CI/CD & Scripting: Building and automating robust CI/CD workflows using Python, Jenkins, and Git.</li></ul>

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