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Metro location, mid-level experience, and popular DevOps role balanced by niche MLOps requirements.
Core DevOps and cloud skills transfer across industries, but agentic ML and media experience increases domain specificity.
Explicit 4–8 years plus mandatory DevOps/MLOps, cloud, Kubernetes, CI/CD, and monitoring skills.
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Build and maintain CI/CD pipelines for deploying agent and ML models reliably.
Manage containerized applications using Docker/Kubernetes across cloud and on-prem environments.
Implement monitoring, logging, alerting, and optimize system performance for a multi-agent media tool.
4 to 8 years of relevant work experience in DevOps/MLOps engineering.
Hands-on experience with containerization (Docker/Kubernetes) and cloud platforms (AWS, Azure, GCP).
Proficiency in CI/CD tools like GitHub Actions, Jenkins, or ArgoCD.
Strong scripting skills in Python and Bash, plus experience with monitoring tools (Prometheus, Grafana, ELK).
Experience or strong interest in multi-agent orchestration frameworks (e.g., LangChain, AutoGen, CrewAI).
Background or exposure to media/content-driven environments and knowledge of distributed/event-driven systems.
Detail-oriented focus on system reliability, scalability, and cost-efficiency, able to work in dynamic, cross-functional teams.