ML Engineer (Azure ML)

Position: ML Engineer (Azure ML) - Remote    

Client: CoForge

Duration: 6-12 months

Location: 100% Remote

Rate: 10$/hr   

Working Hours – India Day Shift

MUST HAVE SKILLS: Azure ML Studio, MLE, MLflow, AKS Clusters, Azure DevOps

We are seeking an experienced(6-8 years) Azure ML / MLOps Engineer with strong expertise in designing, deploying, and operationalizing enterprise-scale AI/ML and Generative AI solutions on Microsoft Azure. The ideal candidate will have hands-on experience with Azure Machine Learning Studio, AKS, Azure Data Factory, Azure DevOps pipelines, and modern MLOps practices for scalable and production-grade machine learning deployments.Key Responsibilities:• Design, develop, and deploy AI/ML and Generative AI solutions using Azure Machine Learning Studio.• Register, manage, and deploy machine learning and AI models within Azure ML environments.• Build and maintain scalable model training, inference, monitoring, and data processing pipelines using Azure ML services.• Deploy and manage machine learning workloads on Azure Kubernetes Service (AKS) clusters.• Develop and optimize end-to-end MLOps workflows following enterprise best practices.• Implement CI/CD pipelines for machine learning projects using Git and Azure DevOps.• Manage model lifecycle processes including experiment tracking, artifact logging, versioning, and deployment using MLflow.• Monitor production models for performance, drift detection, reliability, and operational stability.• Collaborate with data scientists, ML engineers, and DevOps teams to streamline deployment and operationalization processes.• Ensure code quality and maintainability through Python best practices, dependency management, linting, formatting standards, and automated code review tools such as Black and Flake8.• Support data engineering activities including data ingestion, transformation, and pipeline orchestration using Azure Data Factory and Blob Storage.• Troubleshoot deployment, performance, and operational issues across AI/ML environments.

Required Skills & Experience:• Strong hands-on experience with Microsoft Azure services including:

Azure Machine Learning Studio

Azure Kubernetes Service (AKS)

Azure Blob Storage

Azure Data Factory (ADF)

Azure DevOps (ADO) Pipelines

* Experience deploying and managing ML/AI/GenAI models in enterprise environments.• Strong understanding of model deployment and orchestration within AKS clusters.• Experience designing scalable ML pipelines for training, inference, monitoring, and automation.• Strong Python programming skills including environment setup, package management, coding standards, and automation practices.• Familiarity with code quality and formatting tools such as Black, Flake8, and linting frameworks.• Hands-on experience with MLflow for experiment tracking, model registry, logging, and monitoring.• Strong understanding of MLOps principles and machine learning operationalization best practices.• Experience implementing CI/CD workflows using Git and Azure DevOps.• Experience with model monitoring, drift detection, and performance optimization.• Basic to intermediate understanding of data engineering concepts and workflows.

Nice to Have:• Experience with Docker and containerized deployments.• Exposure to distributed computing or scalable AI infrastructure.• Knowledge of cloud-native security and governance practices for AI/ML platforms.Please add how soon they can join if selected for the project.