Senior Staff Engineer: MLOps

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