Jobs at Nvidia in Japan, Yokohama

NVIDIA is looking for Senior Cloud

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.

What you'll be doing:

• Lead the hands-on analysis, optimization, and performance tuning of complex GPU-accelerated systems and AI workloads, ensuring high availability and efficiency across customer data centers.

• Engage with NVIDIA strategic customers to drive AI infrastructure initiatives, support deployment success, and influence long-term platform adoption.

• Serve as a senior technical authority on NVIDIA GPU, DPU, and networking technologies, contributing to architecture reviews and guiding infrastructure decisions at scale.

• Collaborate with internal Engineering, Product, and Sales teams to align customer deployments with NVIDIA’s technology roadmap and business objectives.

• Establish and refine monitoring and optimization methodologies using analytics, telemetry, and automation to detect bottlenecks and improve infrastructure resiliency.

• Participate in post-deployment reviews, incident retrospectives, and strategic planning sessions to shape the customer experience and feed insights into NVIDIA’s infrastructure strategy.

• Complete and lead complex technical projects from initial design through implementation and continuous improvement, ensuring alignment to SLAs and mitigation of technical risks.

• Support business growth by identifying AI infrastructure opportunities in cloud and enterprise environments and driving technical initiatives that showcase NVIDIA’s leadership in this space.

What we need to see:

• 10+ years of experience in large-scale data center service operations with a focus on infrastructure performance, backed by a Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field.

• Strong analytical, solving problems, and decision-making skills, capable of identifying root causes, driving continuous improvement, and delivering resilient technical solutions.

• Strong communication, time management, and organizational skills, with the ability to lead complex projects, guide technical teams, and meet important metrics.

• Preferred certifications in data center, server, or networking technologies, and a willingness to travel up to 25% for customer engagements and team collaboration.

• Proficiency in system-level aspects, encompassing Operating Systems, Linux kernel drivers, GPUs, NICs, and hardware architecture.

• Demonstrated expertise in cloud orchestration software and job schedulers, including platforms like Kubernetes, Docker Swarm, and HPC-specific schedulers such as Slurm.

• Familiarity with cloud-native technologies and their integration with traditional infrastructure is crucial.

• Proficiency in both Japanese and English, with the ability to communicate complex technical topics clearly across multicultural teams and with customers.

Ways to stand out from the crowd:

• Deep familiarity with AI infrastructure and workflows, including training/inference pipelines, MLOps/DevOps tools, containerization (Docker, Kubernetes), and large-scale system deployments.

• Knowledge of data center infrastructure operations, including safety, security, environmental controls, and standard operating procedures.

• Proven expertise in scaling complex systems, with deep experience in automation, orchestration, and performance optimization across compute, storage, and networking layers.

• Good interpersonal and collaboration skills, with the ability to lead discussions, influence outcomes, and build positive relationships with both internal and external collaborators.

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.

• 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

• 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.

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.