Job Description

Role 1 : 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

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