Senior Staff Engineer: MLOps
5 hours ago
Job Title: Senior Staff Engineer MLOps
Location: Bangalore, India
Work Type: Hybrid (part remote, part onsite)
Experience: 11-15 years
Employment Type: Full-time
Role Overview
We are looking for a Senior Staff Engineer MLOps to design, build, and maintain end-to-end ML pipelines. You will work with Data Scientists, Data Engineers, and DevOps teams to productionize ML models and ensure they run efficiently, securely, and reliably in Azure cloud environments.
Key Responsibilities
Build and maintain ML pipelines for data preprocessing, model training, testing, and deployment.
Collaborate with Data Scientists to productionize ML models in Azure ML and Databricks.
Implement CI/CD pipelines for ML workflows using Azure DevOps, GitHub Actions, or Jenkins.
Automate infrastructure provisioning with Terraform, ARM Templates, or Bicep.
Deploy and monitor ML models using Azure Monitor, Application Insights, Prometheus, Grafana, MLflow.
Implement model versioning, experiment tracking, and artifact management.
Ensure security, compliance, and cost optimization for deployed ML solutions.
Develop alerts and monitoring for model drift, data drift, and performance degradation.
Work cross-functionally with Data Engineers, DevOps Engineers, and Data Scientists to streamline ML delivery.
Required Skills
Programming: Python (mandatory), SQL
MLOps / DevOps Tools: MLflow, Azure DevOps, GitHub Actions, Docker, Kubernetes (AKS)
Azure Services: Azure ML, Azure Databricks, Azure Data Factory, Azure Storage, Azure Functions, Azure Event Hubs
CI/CD: Designing pipelines for ML workflows
Infrastructure as Code (IaC): Terraform, ARM Templates, Bicep
Data Handling: Azure Data Lake, Blob Storage, Synapse Analytics
Monitoring & Logging: Azure Monitor, Prometheus, Grafana, Application Insights
ML Lifecycle: Data preprocessing, model training, deployment, monitoring
Preferred Skills
Deploying ML models on Azure Kubernetes Service (AKS)
Knowledge of feature stores and distributed training frameworks
Familiarity with RAG (Retrieval-Augmented Generation) pipelines and LLMOps
Relevant Azure certifications (AI Engineer, Data Scientist, DevOps Engineer)
Other Details
Travel: Up to 10%
Time Type: Full-time
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