Job Description
Position: ML Engineer (Azure ML)
Location: 100% Remote
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.
Share your Resume at as*****1@fc***d.com
Job Classification
Industry: IT Services & Consulting
Functional Area / Department: Other
Role Category: Other
Role: Other
Employement Type: Full time
Contact Details:
Company: FCS Software Solutions
Location(s): Noida, Gurugram
Keyskills:
Azure ML Studio
Azure Data Factory
MLE
MLflow
Azure Blob Storage
AKS Clusters
Azure DevOps
Azure Kubernetes Service