Jobs at NVIDIA

Leads technical engagements with enterprise customers, OEMs, and partners to design, validate, and deploy scalable NVIDIA AI solutions. Advises customers on hardware and software architecture, runs proofs of concept and demos, writes code for data pipelines and AI model training, and deploys solutions on container orchestrators. Drives platform adoption, resolves complex technical issues, enables partners, and influences NVIDIA product and engineering priorities.

Designs, deploys, and maintains large-scale AI and HPC cloud infrastructure for enterprise and research customers. Responsibilities include Kubernetes platform optimization, Linux and storage administration, automation, monitoring, troubleshooting, solution architecture, customer engagements, technical documentation, proof-of-concept activities, and collaboration with engineering, product, and sales teams. The role also provides strategic guidance on DevOps, GPU-accelerated computing, networking, cluster operations, and long-term infrastructure decisions.

Designs and deploys large-scale NVIDIA Neo Cloud infrastructure architectures across data center providers, OEMs, and cloud partners. Serves as a trusted technical advisor, leading solution design, validation, troubleshooting, deployment planning, documentation, and customer engagements. Partners with engineering, product, services, and post-sales teams to address technical gaps, improve operational excellence, and guide long-term infrastructure decisions. Requires deep HPC, AI, GPU, networking, storage, and data center architecture expertise.

Lead end-to-end planning, design, deployment, commissioning, and operational handoff of AI/HPC data center infrastructure. Review customer designs, coordinate power, cooling, controls, cabling, construction, and integration activities, develop readiness audits, resolve deployment issues, and ensure alignment with NVIDIA reference architectures. Serve as a technical advisor to customers and partners, build deployment ecosystems, mentor engineering teams, and drive improvements in reliability, scalability, efficiency, and automation.

Provides senior-level technical support for Ethernet networking, Linux systems, servers, and large-scale AI infrastructure. Investigates complex customer issues, performs diagnostics and root-cause analysis, coordinates critical escalations, and leads high-severity incidents. Advises enterprise and cloud customers, collaborates with Engineering and Product teams, improves documentation and support processes, and applies automation and agentic AI tools to troubleshooting and operational efficiency.

Designs and delivers NVIDIA-based generative AI solutions for enterprise customers and partners. Responsibilities include leading technical engagements, developing proofs of concept and demonstrations, writing Python for data and AI pipelines, designing scalable architectures, deploying workloads on Kubernetes, enabling customers through training, and coordinating engineering, product, sales, and external stakeholders. The role requires expertise in data science, deep learning, LLMs, RAG, agentic AI, LangChain, LangGraph, GPUs, and customer-facing technical consulting.

Owns NVIDIA’s ANZ consumer business across graphics cards and PC systems. Manages OEM, add-in-card, distributor, and reseller relationships; drives revenue, market share, business planning, forecasting, pricing, inventory, product launches, and go-to-market execution. Develops AI PC, gaming, workstation, creator, and edge AI opportunities while coordinating product, marketing, supply, operations, and sales teams.

Design, deploy, operate, and optimize large-scale AI, HPC, cloud, Kubernetes, networking, storage, and infrastructure platforms. Automate deployment, monitoring, alerting, and resource management while resolving issues across the full technology stack. Develop operational standards, documentation, and runbooks; support proofs of concept and upgrades; and provide strategic technical leadership and consultative guidance to enterprise, research, government, academic, and cloud customers.