Jobs at NVIDIA

Design, develop, and deploy AI-powered automation for hardware performance verification. Build intelligent tools and agents for test generation, regression detection, failure analysis, and corrective recommendations. Integrate LLM assistants, create verification data pipelines, establish impact dashboards, and collaborate with verification engineers. Apply generative AI, reinforcement learning, and formal methods to improve coverage, reduce cycle times, and increase productivity across complex GPU, CPU, memory, and HPC verification workflows.

Support and develop large-scale OpenStack cloud infrastructure across multi-site deployments. Troubleshoot OpenStack services, PXE provisioning, networking, distributed systems, and third-party dependencies. Collaborate with SRE, platform, software, data center, and product teams to improve deployment quality, reliability, and time to market. Contribute Python and automation code while monitoring, investigating KPIs, resolving incidents, and supporting NVIDIA’s global engineering infrastructure.

Build and improve CI/CD pipelines, release automation, deployment workflows, infrastructure-as-code, and DevOps tooling. Triage pipeline issues, automate manual processes, maintain documentation and runbooks, support data center infrastructure, and improve platform security through hardening and credential management. Collaborate with globally distributed SRE and development teams, providing primary DevOps support during India business hours and coordinating handoffs to U.S.-based teams.

Provides Tier 3 technical support for networking products in data center, AI, storage, and HPC environments. Installs systems, troubleshoots complex network issues, develops customer solutions, manages complex installations, and handles problem resolution. The role requires expertise in routing, switching, virtualization, Linux, scripting, Ansible, and major network vendors. It also involves customer communication, site visits, process improvement, and collaboration with Engineering, Marketing, Support, customers, and partners.

Own and resolve complex Slurm support cases for production AI and HPC clusters. Diagnose scheduler, Linux, networking, storage, authentication, database, container, and GPU infrastructure issues; advise customers on configuration, upgrades, reliability, and incident recovery; collaborate with engineering on defects; and develop technical documentation, diagnostic tools, and training.

Design, develop, operate, and optimize large-scale software-defined networking solutions for NVIDIA AI Cloud environments. Responsibilities include building OVS/OVN control and data plane software, Kubernetes networking services, observability systems, CI/CD pipelines, GitOps integrations, and secure gRPC/REST services. The role owns production reliability, incident response, performance tuning, and upstream open-source contributions while collaborating with SRE, DevOps, and network engineering teams.

Supports and operates NVIDIA’s large-scale on-premises and cloud network infrastructure in a 24/7 global operations environment. Responsibilities include monitoring alerts, resolving incidents within SLAs, troubleshooting network issues, managing IP infrastructure and datacenter interconnects, coordinating vendors, implementing upgrades and capacity expansions, improving operational workflows, and documenting best practices. The role requires extensive networking protocol knowledge, cloud experience, automation exposure, and strong incident-management and communication skills.