Jobs at NVIDIA

Lead the design, architecture, deployment, optimization, and maintenance of large-scale enterprise cloud, WAN, and data center networks. Manage global site deployments from requirements through operational handover, automate network workflows with Python and Ansible, troubleshoot complex network issues, maintain documentation, and coordinate internal teams and vendors. Own project timelines, resources, budgets, and delivery while implementing modern routing, switching, firewall, load-balancing, and data center technologies.

Build NeMo Evaluator and agentic AI infrastructure using Python APIs, SDKs, plugins, and evaluation workflows. Develop systems for agent execution data, regression detection, observability, reliability, and performance across distributed, cloud-native environments. Collaborate across research, product, platform, and infrastructure teams while providing technical leadership, mentoring, and ownership of complex cross-component problems.

Lead software and system architecture for NVIDIA’s cloud networking, security, DPU, and NIC technologies. Responsibilities include designing end-to-end hardware-to-application solutions, researching technologies, writing architecture specifications, developing proof-of-concept prototypes, solving complex technical problems, and collaborating with global engineering, product, customer, and field teams. The role requires strong C and Python development, Linux, cloud networking, networking protocols, and systems architecture experience.

Build, validate, deploy, tune, monitor, and retire high-confidence security detections across SIEM, endpoint, cloud, identity, SaaS, developer, and AI environments. Translate incidents, threat intelligence, hunts, and red-team findings into tested detection logic. Improve detection-as-code workflows, telemetry quality, coverage tracking, and alert context while reducing false positives. Partner with responders and security teams, conduct reviews, document operational content, and coach analysts and engineers.

Develop platform software using container runtimes and Kubernetes to enable GPU-accelerated applications. Design systems software for container orchestration, cloud-native environments, and distributed systems. Integrate software across NVIDIA engineering teams while addressing performance, security, reliability, and evolving priorities. The role involves Rust and Go development, Linux system internals, container sandboxing, confidential computing, virtualization, and GPU resource management.

Create and deliver developer-focused technical content and workshops that teach CUDA and NVIDIA GPU technologies. Evaluate new CUDA features, produce tutorials and blog posts, capture developer feedback to inform product decisions, and collaborate across product, engineering, and marketing teams to drive developer adoption.

Research and implement GPU-acceleration techniques for high-performance databases and ETL. Analyze and optimize data-intensive workloads, collaborate with hardware, systems, and research teams to influence next-generation architectures and programming models, and publish/share findings with customers and the community.

Lead architecture for cloud-networking and design system architectures for DPUs and NICs. Build end-to-end solutions from application to hardware, write architecture specifications, evaluate new technologies, develop POCs, and collaborate globally with SW/HW teams and customers.

Provide advanced technical support for NVIDIA InfiniBand, NVLink and GPU-based HPC/AI infrastructure. Troubleshoot installations, networking and interoperability issues on multi-distro Linux, reproduce and resolve customer problems, use packet analysis and cluster tools, and collaborate with engineering, marketing, and support teams to improve processes and documentation.

Prototype and integrate GPU-accelerated distributed data processing, compression, databases, and analytics solutions. Optimize complex data-intensive workloads across heterogeneous CPU/GPU architectures, collaborate on next-generation hardware and software designs, and work with customers and cloud service providers to deploy solutions and influence open standards. The role requires deep expertise in parallel programming, C/C++, accelerator architecture, memory systems, and compression or distributed data systems.

Lead architecture for cloud networking and security solutions involving DPUs and NICs. Design end-to-end systems from application to hardware, define architecture specifications, evaluate technologies, develop proof-of-concept prototypes, and collaborate with global software, hardware, product, engineering, and customer teams. The role requires strong C and Python development, Linux, networking protocols, cloud technologies, and systems architecture expertise.

Designs and deploys large-scale AI and HPC GPU cloud infrastructure for NVIDIA Cloud Partners. Serves as the primary technical advisor across solution design, development, integration, production, debugging, and customer adoption. Builds proof-of-concepts, integrates AI software stacks, libraries, frameworks, and models, and delivers technical presentations and workshops. Partners with engineering, product, sales, and business teams to secure opportunities, guide product strategy, and support complex customer engagements throughout the lifecycle.

Build and lead development of NVIDIA’s open-source NeMo Core Platform for executing, evaluating, deploying, and optimizing agentic AI systems across local, Docker, Kubernetes, Slurm, on-premises, and air-gapped environments. Design platform APIs, plugins, SDKs, job orchestration, authentication, RBAC, observability, testing, and reliability features. Provide technical leadership through architecture and code reviews, mentoring, and ownership of complex cross-component problems.

Lead NVIDIA’s RL post-training frameworks strategy and engineering ecosystem across distributed training, inference, rollout, evaluation, orchestration, and NVIDIA platforms. Build and manage globally distributed teams, prioritize upstream and internal investments, establish benchmarks and execution metrics, and drive reliable open-source integrations. Partner with research, product, hardware, CUDA, networking, and external communities to scale reinforcement learning workloads across GPUs and heterogeneous systems.

Design and implement LLM-first APIs and documentation for CUDA-X math libraries. Develop tools, metrics, and processes to improve AI-agent code generation and transform library APIs into LLM-friendly formats. Collaborate with stakeholders on LLM-enhanced releases while prototyping solutions for code-generation platforms. Requires expertise in LLMs, fine-tuning, reinforcement learning, RAG, MCP, agent tooling, composable API design, and technical documentation.

Design, develop, integrate, test, and productize perception software for autonomous driving systems. Responsibilities include implementing robust and reusable software components, deploying deep neural network models to embedded real-time platforms, developing verification plans, debugging systems, maintaining documentation, and analyzing real or synthetic benchmark data. The role requires close collaboration with perception engineers and researchers throughout the software development lifecycle.

Support NVIDIA enterprise customers using GPU-accelerated platforms, triage hardware and AI/ML workload issues, collaborate with engineering teams, and drive cases through resolution. Develop support tools and products using AI, document customer interactions, and troubleshoot Linux-based multi-GPU systems, firmware, kernels, drivers, containers, and distributed workloads. The role also requires customer communication, technical analysis, and occasional weekend or holiday support.

Lead relationships with major research universities, advising institutional leaders, research computing teams, and principal investigators on NVIDIA technologies. Drive business growth, revenue forecasting, go-to-market strategy, platform adoption, and ecosystem enablement. Build partnerships across scientific disciplines, coordinate internal technical and product teams, communicate technology roadmaps, and develop expertise in emerging computational methods. Travel approximately 25% or more and support institutions in the Northeast or Mid-Atlantic regions.

Develop and support NVIDIA networking technologies for AI clusters, including InfiniBand, NVLink, and Spectrum-X. Reproduce and root-cause complex customer issues down to source code, collaborate with R&D on fixes, analyze high-performance network metrics, and create diagnostic tools. The role requires extensive C and Python development in Linux and embedded systems, networking expertise, customer support experience, and strong communication skills. Occasional weekend or holiday support may be required.

Leads NVIDIA’s US Medtech Account Managers and drives enterprise sales growth across named manufacturing accounts. Responsibilities include demand generation, forecasting, executive relationship development, channel and partner collaboration, revenue target attainment, and coordination with internal teams to address customer needs. The role focuses on selling NVIDIA hardware and software for AI and accelerated computing in healthcare and medtech markets.