ML Operations Engineer

MLOps Engineer (Azure)

Location: Ahmedabad, Gujarat

Experience: 3–5 Years of Experience

Immediate joiner will be preferred.

Job Summary:

We are seeking a skilled and proactive MLOps Engineer with strong experience in the Azure ecosystem to join our team. You will be responsible for streamlining and automating machine learning and data pipelines, supporting scalable deployment of AI/ML models, and ensuring robust monitoring, governance, and CI/CD practices across the data and ML lifecycle.

Key Responsibilities: MLOps:

·      Design and implement CI/CD pipelines for machine learning workflows using Azure DevOps, GitHub Actions, or Jenkins.

·      Automate model training, validation, deployment, and monitoring using tools such as Azure ML, MLflow, or KubeFlow.

·      Manage model versioning, performance tracking, and rollback strategies.

·      Integrate machine learning models with APIs or web services using Azure Functions, Azure Kubernetes Service (AKS), or Azure App Services.

DataOps:

·      Design, build, and maintain scalable data ingestion, transformation, and orchestration pipelines using Azure Data Factory, Synapse Pipelines, or Apache Airflow.

·      Ensure data quality, lineage, and governance using Azure Purview or other metadata management tools.

·      Monitor and optimize data workflows for performance and cost efficiency.

·      Support batch and real-time data processing using Azure Stream Analytics, Event Hubs, Databricks, or Kafka.

Required Skills:

·      Strong hands-on experience with Azure Machine Learning, Azure Data Factory, Azure DevOps, and Azure Storage solutions.

·      Proficiency in Python, Bash, and scripting for automation.

·      Experience with Docker, Kubernetes, and containerized deployments in Azure.

·      Good understanding of CI/CD principles, testing strategies, and ML lifecycle management.

·      Familiarity with monitoring, logging, and alerting in cloud environments.

·      Knowledge of data modeling, data warehousing, and SQL. 

Preferred Qualifications:

·      Azure Certifications (e.g., Azure Data Engineer Associate, Azure AI Engineer Associate, or Azure DevOps Engineer Expert).

·      Experience with Databricks, Delta Lake, or Apache Spark on Azure.

·      Exposure to security best practices in ML and data environments (e.g., identity management, network security).

Soft Skills:

·      Strong problem-solving and communication skills.

·      Ability to work independently and collaboratively with data scientists, ML engineers, and platform teams.

·      Passion for automation, optimization, and driving operational excellence.