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NVIDIA is looking for Senior CloudInfrastructure/DevOps
What you'll be doing:
Maintain large scale HPC/AI clusters with monitoring, logging and alerting Manage Linux job/workload schedulers and orchestration tools.
Develop and maintain continuous integration and delivery pipelines
Develop tooling to automate deployment and management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources.
Deploy monitoring solutions for the servers, network and storage.
Perform troubleshooting bottom up from bare metal, operating system, software stack and application level.
Being a technical resource, develop, re-define and document standard methodologies to share with internal teams Support Research & Development activities and engage in POCs/POVs for future improvements .
What we need to see:
BS/MS/PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields.
At least 8 years of professional experience in networking fundamentals, TCP/IP stack, and data center architecture.
Knowledge of HPC and AI solution technologies, including CPUs, GPUs, high-speed interconnects, and supporting software.
Extensive knowledge and hands-on experience with Kubernetes, including container orchestration for AI/ML workloads, resource scheduling, scaling, and integration with HPC environments.
Experience in managing and installing HPC clusters, including deployment, optimization, and troubleshooting.
Experience with job scheduling workloads and orchestration technologies such as Slurm, Kubernetes, and Singularity.
Excellent knowledge of Windows and Linux systems (Redhat/CentOS and Ubuntu), including internals, ACLs, OS-level security protections, and common protocols like TCP, DHCP, DNS, etc.
Experience with multiple storage solutions, including Lustre, GPFS, ZFS, and XFS. Familiarity with newer and emerging storage technologies is a plus.
Proficiency in Python programming and bash scripting.
Knowledge of CI/CD pipelines for software deployment and automation.
Comfortable with automation and configuration management tools, including Jenkins, Ansible, Puppet/Chef, etc.
Ability to communicate technical concepts and collaborate effectively with Mandarin-speaking customers.
Ways to stand out from the crowd:
Knowledge of CPU and/or GPU architecture .
Knowledge of Kubernetes, container related microservice technologies.
Experience with GPU-focused hardware/software (DGX, CUDA.)
Background with RDMA (InfiniBand or RoCE) fabrics.
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