▷ 3 Days Left! MLops Engineer

Role Overview

We are looking for an experienced MLOps Lead with deep expertise in Azure and AWS cloud ecosystems, who can design, deploy, and manage scalable AI / ML infrastructure. The ideal candidate should bring a strong background in cloud governance, GenAI tooling, automation, and CI / CD pipelines, with hands-on experience across modern MLOps frameworks.

Key Responsibilities

• Design, implement, and manage scalable cloud-based AI / ML infrastructure across Azure and AWS.
• Drive end-to-end MLOps lifecycle — model deployment, monitoring, retraining, and governance.
• Enable GenAI and Agentic AI platforms leveraging Azure OpenAI, Bedrock, Anthropic Claude, LangChain, etc.
• Implement CI / CD pipelines using Azure DevOps or AWS CodePipeline.
• Ensure security, observability, and compliance across ML and GenAI ecosystems.
• Manage infrastructure automation via Terraform, Bicep, CloudFormation, or similar IaC tools.
• Collaborate with data science and engineering teams to optimize ML workflows, data pipelines, and API integrations.
• Implement monitoring and alerting using Grafana, Prometheus, Azure Monitor, and Application Insights.
• Oversee networking, identity management, and role-based access controls (IAM, RBAC) across clouds.
• Support model lifecycle management — drift monitoring, retraining, technical evaluation, and business validation.

Technical Skills & Expertise

Cloud & MLOps Platforms

AI / ML & Programming

DevOps & Infrastructure

Monitoring & Observability

Security & Access Management

Testing & Automation

Good to Have

Preferred Background