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ML Ops Lead

ML Ops Lead

Epergne SolutionsIndore, Madhya Pradesh, India
21 hours ago
Job type
  • Quick Apply
Job description

Job Role : - ML Ops Lead

Job Location : - India

Job Type : - Remote

Experience : -7+ Years

Roles & Responsibilities : -

  • Design, deploy, and manage scalable, secure, and automated ML / AI platforms across Azure and AWS.
  • Lead MLOps lifecycle model deployment, monitoring, retraining, CI / CD orchestration, and drift management.
  • Build, maintain, and optimize ML workflows using Azure Machine Learning, Databricks, and AWS SageMaker.
  • Integrate ML services with data platforms (Azure Data Lake, Cosmos DB, S3, DynamoDB, RDS).
  • Implement governance, observability, compliance, and audit practices across ML and GenAI environments.
  • Manage containerized workloads using Docker and Kubernetes (AKS / EKS).
  • Develop and maintain Infrastructure as Code using Terraform, Bicep, CloudFormation, or CDK.
  • Collaborate with stakeholders to resolve ML pipeline issues and ensure efficient production delivery.
  • Conduct testing (unit / integration) as part of CI / CD pipelines via Azure DevOps or AWS CodePipeline.
  • Apply security best practices RBAC, IAM, least privilege, authentication, and key management.
  • Monitor systems using Grafana, Prometheus, Azure Monitor, and Log Analytics.

Skills & Requirements : -

  • Experience : 7+ years in cloud platform engineering and ML operations.
  • Cloud Platforms : Azure (AI Services, ML, AKS, Functions) and AWS (SageMaker, Bedrock, Lambda).
  • ML & AI : Strong in Python, TensorFlow, PyTorch, Scikit-learn, and end-to-end ML lifecycle management.
  • GenAI Tools : Azure OpenAI, Bedrock, LangChain; understanding of prompt injection and jailbreak mitigation.
  • IaC & DevOps : Hands-on with Terraform, Bicep, CloudFormation, CDK, Azure DevOps, CodePipeline.
  • Security : IAM, RBAC, Azure Policy, AWS SCP, Key Vault, Audit Logging.
  • Networking : DNS, Load Balancers, VPNs, VNets.
  • Monitoring : Grafana, Prometheus, Application Insights, Azure Monitor.
  • Databases : Azure SQL, Cosmos DB, AWS S3, RDS, DynamoDB, Redshift.
  • Preferred Tools : GitHub Copilot, Cursor, Claude Code, M365 Copilot.
  • Soft Skills : Strong problem-solving, stakeholder collaboration, and documentation abilities.
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