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Tier-1 employer, mid-level experience band, and metro location increase applicant competition.
Technical MLOps skills (Azure, Kubernetes, CI/CD) are broadly transferable across industries.
Explicit 2-7 year requirement plus mandatory Azure, Kubernetes, and MLOps tech stack increases filtering.
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Take full ownership of AIops deliverables ensuring quality standards, timelines, and budget adherence.
Design, implement, and manage AIops solutions to automate and optimize AI/ML workflows including monitoring and maintaining production AI/ML systems.
Develop and maintain CI/CD pipelines for AI/ML models and troubleshoot AI/ML infrastructure and workflow issues.
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field.
2-7 years of relevant experience in AIops, MLOps, or related fields.
Strong proficiency in Python and experience with FastAPI; hands-on expertise with Kubernetes (or AKS).
Experience with MS Azure AI/ML services including Azure ML Flow; knowledge of CI/CD tools like Jenkins, GitHub Actions, or Azure DevOps.
Experienced AIops specialist capable of owning end-to-end AI/ML operational workflows and infrastructure.
Hands-on with cloud services (especially Azure) and container orchestration to integrate and maintain AI systems in production.
Comfortable working with DevContainer, CI/CD pipelines, and agile troubleshooting in fast-paced environments.