ML OPS - Lead

5 - 8 years

7 - 12 Lacs

Posted:3 weeks ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Required Skills & Experience

  • 8-10 years of overall experience, including 3+ years in MLOps or DevOps for ML systems.
  • Hands-on expertise with AWS SageMaker model training, endpoint deployment, pipelines, and model registry.
  • Strong experience with AWS services: S3, Lambda, ECR, ECS/EKS, CloudWatch, IAM, Cloud Formation, and AWS CDK.
  • Proven experience in AWS CDK (Cloud Development Kit) using Typescript for infrastructure automation and environment provisioning.
  • Expertise in building and managing CI/CD pipelines for ML workflows (AWS CodePipeline, Jenkins, or GitHub Actions).
  • Proficiency in containerization technologies Docker and Kubernetes.
  • Strong scripting and automation skills using Python, Typescript, and Bash.
  • Experience with monitoring, logging, and drift detection for production ML models.
  • Deep understanding of ML lifecycle management model packaging, versioning, testing, and deployment.
  • Familiarity with data pipelines and collaboration with Data Engineering teams for feature ingestion.
  • Working knowledge of security, compliance, and governance practices in the banking/financial domain.
  • Excellent communication, leadership, and stakeholder management skills across onsiteoffshore teams

Mandatory Competencies
  • Data Science and Machine Learning - Data Science and Machine Learning - AI/ML
  • Cloud - AWS - AWS S3, S3 glacier, AWS EBS
  • Cloud - AWS - AWS Lambda,AWS EventBridge, AWS Fargate
  • Cloud - AWS - AWS SDKs, AWS CLI, AWS CloudFormation, AWS Cloudshell, AWS Cloud Development Kit
  • Beh - Communication
  • Development Tools and Management - Development Tools and Management - CI/CD
  • DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - Basic Bash/Shell script writing
  • DevOps/Configuration Mgmt - DevOps/Configuration Mgmt - Containerization (Docker, Kubernetes).

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