NVIDIA is the world leader in computer graphics, artificial intelligence, and accelerated computing. For over 25 years, we have been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the worlds hardest problems.

NVIDIA is looking for Senior Cloud Infrastructure/DevOps Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups around the world are using NVIDIA products to revolutionize deep learning and data analytics, and to power data centers. Join the team building many of the largest and fastest AI/HPC systems in the world! We are looking for someone with the ability to work on a dynamic customer focused team that requires excellent interpersonal skills. This role will be interacting with customers, partners and internal teams, to analyze, define and implement large scale Networking projects. The scope of these efforts includes a combination of Networking, System Design and Automation and being the face to the customer!

What you'll be doing:

Design, implement and 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 .
Regional travel is required for on-site visits with customers.

What we need to see:

BS/MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields with at least 8 years work or research experience in networking fundamentals, TCP/IP stack, and data center architecture.
Knowledge of HPC and AI solution technologies from CPU’s and GPU’s to high speed interconnects and supporting software.
Direct design, implementation and management experience with cloud computing platforms (e.g. AWS, Azure, Google Cloud).
Experience with job scheduling workloads and orchestration technologies such as Slurm, Kubernetes and Singularity.
Excellent knowledge of Windows and Linux (Redhat/CentOS and Ubuntu) networking (sockets, firewalld, iptables, wireshark, etc.) and internals, ACLs and OS level security protection and common protocols e.g. TCP, DHCP, DNS, etc.
Experience with multiple storage solutions such as Lustre, GPFS, zfs and xfs. Familiarity with newer and emerging storage technologies.
Python programming and bash scripting experience.
Comfortable with automation and configuration management tools including Jenkins, Ansible, Puppet/Chef, etc.
Deep knowledge of Networking Protocols like InfiniBand, Ethernet Deep understanding and experience with virtual systems (for example VMware, Hyper-V, KVM, or Citrix).
Strong written, verbal, and listening skills in English are critical.
Hands-on, adaptable problem-solver with a collaborative approach and strong ability to thrive in fast-paced, dynamic environments, working effectively with cross-functional teams to deliver innovative solutions

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.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you.

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NVIDIA Semiconductor Shanghai

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