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3.0 - 6.0 years

0 - 3 Lacs

Bengaluru, Mumbai (All Areas)

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Role & responsibilities Implement and manage AIOps platforms for intelligent monitoring, alerting, anomaly detection, and root cause analysis (RCA). Possess end-to-end knowledge of VLLM model hosting and inferencing. Advanced knowledge of public cloud platforms such as AWS and Azure. Build and maintain machine learning pipelines and models for predictive maintenance, anomaly detection, and noise reduction. Experience in production support and real-time issue handling. Design dashboards and visualizations to provide operational insights to stakeholders. Working knowledge of Bedrock, SageMaker, EKS, Lambda, etc. 1 to 2 years of experience with Jenkins and GoCD to make build/deploy pipelines. Hands-on experience with open-source and self-hosted model APIs using SDKs. Drive data-driven decisions by analyzing operational data and generating reports on system health, performance, and availability. Basic knowledge of kserve and rayserve inferencing . Good knowledge of high level scaling using Karpenter , Keda , System based vertical/horizontal scaling. Strong knowledge on linux operating system or linux certified . Previous experience with Helm chart deployments and Terraform template and module creation is highly recommended. Secondary Responsibilities: Proven experience in AIOps and DevOps, with a strong background in cloud technologies (AWS, Azure, Google Cloud). Proficiency in tools such as Kubeflow, Kserve, ONNX, and containerization technologies (Docker, Kubernetes). Experience with enterprise-level infrastructure, including tools like terraform, helm, and On-Prem servers hosting. Previous experience in fintech or AI based tech companies are highly desirable. Demonstrates the ability to manage workloads effectively in a production environment. Possesses excellent communication and collaboration skills, with a strong focus on cross-functional teamwork.

Posted 1 day ago

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