(ML OPNS Lead)Machine Learning Operations Lead Engineer

Job Mode : Remote

Experience : 7+ Years

Notice Period : Immediate / 10 to 15 Days

7+ years in platform or infrastructure engineering with significant experience in ML Ops, AI, and Cloud (Azure & AWS).

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• Design, deploy, and manage scalable, secure, and high-performing cloud-based infrastructures across Azure and AWS.
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• Lead end-to-end ML Ops lifecycle , including model deployment, monitoring, retraining, and CI/CD integration.
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• Collaborate with AI/ML, Data Science, and DevOps teams to automate model lifecycle management and streamline ML workflows.
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• Architect and implement governance, compliance, observability, and security frameworks for ML and GenAI systems.
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• Drive innovation in Generative AI and Agentic AI ecosystems , integrating services like Azure OpenAI, Bedrock, Anthropic Claude, and OpenAI API.
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• Implement infrastructure-as-code (IaC) practices using Terraform, Bicep, ARM, or CloudFormation .
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• Manage networking, IAM, and security configurations across Azure and AWS environments.
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• Establish monitoring, alerting, and performance dashboards using Grafana, Prometheus, Azure Monitor, and Log Analytics .
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• Azure: Azure AI Services, Azure Search, Azure ML, Databricks, AKS, Azure AI Foundry, Azure AI Hub.
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• AWS: SageMaker, Bedrock, Lambda, ECS, CDK, CloudFormation.
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• Exposure to Generative and Agentic AI ecosystems (Azure OpenAI, Bedrock, Claude, LlamaCloud, LangChain).
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• Understanding of token usage, prompt injection, jailbreak risks , and mitigation methods.
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• Experience with Azure AI Evaluation SDK and AI Red Teaming Prompt Security Scans .
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• Hands-on experience with Python ML libraries (TensorFlow, PyTorch, Scikit-learn).
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• Strong experience with Azure DevOps / AWS CodePipeline for CI/CD setup and management.
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• Familiarity with Docker , Kubernetes , and container orchestration.
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• Knowledge of IaC tools (Terraform, ARM/Bicep, CloudFormation).
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• Azure Blob Storage, Cosmos DB, SQL, Key Vault, Data Lake Storage.
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• AWS S3, DynamoDB, RDS, Redshift, Aurora.
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• Understanding of OLTP and OLAP systems .
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• Proficiency in DNS, VPNs, Load Balancing, VNets, IAM , and access control (RBAC, SCP, Azure Policy).
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• Familiarity with Microsoft AD and principles of least privilege.
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• Hands-on with KMS , Key Vault , and identity governance best practices.
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• Experience using Azure Machine Learning Studio, SDK (v2), CLI (v2) for model monitoring, retraining, and deployment.
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• Build and optimize end-to-end ML workflows for production environments.
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• Implement drift monitoring , model retraining , and technical & business validation processes.
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• Collaborate with data scientists for model deployment and performance optimization.
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• Experience with code assistant tools (GitHub Copilot, Cursor, Claude Code).
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• Familiarity with Azure Bot Framework, APIM, Application Gateway .
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• Exposure to M365 Copilot and related ecosystem tools.
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• Proficiency with AWS Python SDK (Boto3) and AWS CDK .
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• Implement unit and integration testing in CI/CD workflows (preferably using ADO).
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• Ensure testing and validation coverage for ML pipelines and infrastructure deployments.
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• Bachelor s or Master s in Computer Science, Information Technology, or related field.
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• Certification(s) in Azure AI Engineer, AWS Machine Learning Specialty , or DevOps highly desirable.
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