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Strong employer brand and Mumbai location increase competition, but niche MLOps/agent skills moderate applicant density.
MLOps and DevOps infrastructure focus gives moderate transferability across industries.
Requires specific MLOps, Kubernetes, cloud, CI/CD, and monitoring skills but no explicit years requirement.
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Own reliable deployment, monitoring, and scaling of multi-agent media tools with focus on infrastructure, automation, and performance optimization.
Build and maintain CI/CD pipelines for agent and model deployments using containerization (Docker/Kubernetes) and manage cloud/on-prem environments.
Collaborate with engineers and data scientists to streamline model deployment, retraining, and ensure compliance with security and data governance policies.
Strong background in DevOps/MLOps with hands-on experience in cloud platforms (AWS, Azure, GCP) and Kubernetes.
Proficiency with CI/CD tools such as GitHub Actions, Jenkins, ArgoCD and scripting in Python and Bash.
Experience implementing monitoring tools like Prometheus, Grafana, or ELK stack for system performance and alerting.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in agentic frameworks (e.g., LangChain, AutoGen, CrewAI) and AI deployment pipelines, preferably with media or content-driven environment exposure.
Detail oriented with a proactive approach to identifying system bottlenecks and optimizing for reliability, scalability, and cost efficiency.
Able to collaborate effectively across cross-functional teams in dynamic, agile environments focused on advanced analytics and AI solutions.