ML Engineer (Azure ML | MLOps | Generative AI)

ML Engineer (Azure ML | MLOps | Generative AI) Experience: 5+ Years Location: Remote (Candidates should be willing to visit the Chennai or Bengaluru office once a month, if required.) Employment Type: Full-time Roles & Responsibilities Design, develop, and deploy Machine Learning models on Azure. Build and maintain ML pipelines and data processing workflows. Develop Generative AI and LLM-based applications using RAG, Prompt Engineering, and AI Agents. Fine-tune Large Language Models (LLMs) using modern techniques. Implement MLOps practices including model deployment, monitoring, and lifecycle management. Build CI/CD pipelines for ML solutions using GitHub Actions. Manage cloud infrastructure using Terraform, Bicep, or Pulumi. Deploy and manage applications using Docker and Kubernetes. Monitor deployed models using Azure Monitor and observability tools. Collaborate with Data Scientists, Software Engineers, and DevOps teams. Ensure AI solutions follow Responsible AI, security, and governance best practices. Required Skills 5+ years of experience as an ML Engineer. Hands-on experience with Azure Machine Learning (Azure ML). Strong programming skills in Python. Experience with Machine Learning libraries such as Scikit-learn, TensorFlow, or PyTorch. Strong knowledge of MLOps concepts and Azure ML pipelines. Experience with Docker, Kubernetes, and Git. Hands-on experience with GitHub Actions for CI/CD. Infrastructure as Code using Terraform, Bicep, or Pulumi. Experience with Generative AI, LLMs, RAG, Prompt Engineering, and AI Agents. Strong SQL and data engineering fundamentals. Knowledge of Azure Monitor and model monitoring. Good understanding of cloud security and Azure services. Preferred Skills Azure Certifications. Experience with Vector Databases. Experience building production-scale AI applications. Knowledge of Spark, Hadoop, or cloud data platforms. Qualification Bachelor's degree in Computer Science, Information Technology, or a related field. Work Mode Remote. Candidates should be available to visit the Chennai or Bengaluru office once a month , if required.