Role : ML Lead :

Lead Responsibilities :

- Lead design and implementation of scalable CI/CD pipelines and deployment workflows.

- Drive operational excellence across DevOps, ML Ops, automation, and observability.

- Manage end?to-end model lifecycle : registering, inferencing, endpoint optimization.

- Monitor incident management (ICMs), RCA, and DRI responsibilities.

- Mentor engineers on debugging, scripting, DevOps, and reliability best practices.

- Guide automation initiatives to improve resilience, reduce manual work, and increase delivery velocity.

- Collaborate with cross-functional teams on architecture, release planning, and operational governance.

- Establish and maintain governance, compliance, and production-readiness standards.

- SPOC for all stakeholder interactions.

Technical Skills required :

- Programming : Python / C# (either of one is mandatory).

- Ops & Reliability : DRI workflows, Incident Management (ICMs), production triaging.

- ML Operations : Model registering, inferencing, endpoint configuration & optimization.

- DevOps & Containerization : Docker, Git, CI/CD pipelines, Azure DevOps (ADO).

- Cloud & Infrastructure : Microsoft Azure, Azure Blob Storage, AML Studio.

Good to have :

- Data & Analytics : Kusto Query Language (KQL), ADX Dashboards.

- Inference Optimization : vLLM for high performance LLM serving.

- Automation & Monitoring : Ops monitoring, deployment automation, pipeline orchestration.