PCAI CoE Engineer

1 month ago

bangalore, India Taggd Full time
Key responsibilities of a PCAI CoE Engineer may include.
Resolution of complex problems in enterprise and mission-critical customers of PCAIAssess and appreciate technical issues and customers' business impact, and manage technical communication with customers and other stakeholders.Providing leadership in complex technical problem management, working closely with end customers and HPE remote and field support staffIdentifying and resolving customer issues, particularly with NVIDIA GPUs and related infrastructure components critical to AI processing.Troubleshooting and resolving issues with AI workflows leveraging CUDA, cuDNN, TensorRT, and NVIDIA Deep Learning frameworks.Provide technical expertise in deep learning model deployment using NVIDIA GPUs in cloud and on-premise environments.Work with stakeholders to identify opportunities for leveraging AI technologies to drive business solutions.Troubleshoot and resolve performance bottlenecks in AI workflows involving NVIDIA GPU acceleration.Technical support of support of Kubernetes (K8s) environments, and well-versed in AI tooling such as Apache Airflow for data orchestration and MLFlow for machine learning lifecycle management.Troubleshoot and optimize AI applications and infrastructure for maximum efficiency and minimal downtime.Fault isolation, Problem reproduction, interacting with the engineering teams, QA, and development engineers, Escalation and Elevation managementDevelopment of knowledge content and runbooksKnowledge & Skills Required
AI/ML SkillsGood understanding of AI/ML and Analytics applications such asKubeflow & MLflow, MLOPS – Tool (any Tools)Apache Sparck and SupersetRay, Feast, EzPresto data source,Data LakeMlops Frame WorksMLDE (Determined AI) -optioNVIDIA AI Enterprise NIM Microservices, Models, LLM, CUDANVIDIA Neural Modules (NeMo) - optionalExcellent knowledge on below platform componentsLinux operating system (RHEL 8/Rocky/Ubuntu/Centos/Suse)Kubernetes, container runtimes and Container networking, Creating Docker ImagesTroubleshooting K8s Cluster issueEzmeral-specific Kubernetes: ezkube, ezfab etc.Single Sign-on and IAMPostgres database - optionHelm, Istio and Spire – (Istio – Service Mesh)Storage and CSI, CNI, operators (File Storage/ Block Storage/Object Storage)Troubleshooting experience on CSI & CNIContainer base storage access protocol
NVIDIA GPU, NVIDIA AI and related software’sGood Knowledge of GPU technologies, NVIDIA GPU operator, NVIDIA vGPU technologyStrong GPU Understanding and troubleshooting skills at the HW, OS, SW and Application layers.Experience with NVIDIA SDKs (e.g., DeepStream, Jetson, etc.) and GPU performance tuning.Experience with NVIDIA Jetson for edge AI development.Knowledge of MLOps and experience with AI model deployment pipelines.Familiarity with containerization and deployment using Docker and Kubernetes on GPU-powered systems.Familiarity with NVIDIA’s AI software stack, including Triton Inference Server, NVIDIA Clara, and NVIDIA Isaac and scalable AI workflows leveraging CUDA, cuDNN, TensorRT, and NVIDIA Deep Learning frameworksExperience with cloud platforms such as AWS, Azure, or Google Cloud for NVIDIA GPU-based AI model deployment.performance profiling, tuning, and optimization of AI applications on NVIDIA GPUs.OS, Networking & VirtualizationExcellent understanding ofVMware vCenter + ESXi 7 & 8, , Switching. Layer 2 Networking, Cluster managementHA, DRSStorage access protocol for VMwareContent libraries and OVA/Template management & deploymentQumless OSVMware VMFS datastore managementKnowledge on VMware standard vswitches, VMkernel interfaces and VDS would be a bonusNFS storage configuration and troubleshooting would be desired
Other skillsGood knowledge and hands-on experience with at least two various Linux distributions like RHEL, SLES, Ubuntu, and Debian.Knowledge and experience with Linux System Administration, package management, scheduling, boot procedures/troubleshooting, performance optimization, and networking concepts.Windows AD administration (user management for EZ authentication integration)IPV6 + SLAACCommon skills and qualificationsEducation: A bachelor's or master's degree in computer science, information technology, or a related field is preferred.Problem-Solving Skills: Excellent problem-solving skills and the ability to diagnose and resolve complex technical issues.Communication Skills: Effective communication skills to collaborate with other teams, including development, security, and compliance teams.Collaboration Skills: The ability to work effectively in a team environment and to coordinate efforts with other teams to resolve issues and implement new solutions.IT Service Management Experience: Familiarity with IT service management (ITSM) frameworks, such as ITIL, and experience with incident, problem, and change management processes.

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