Jobs at NVIDIA

Conduct offensive security research against GPU firmware, microcode, kernel drivers, and embedded software. Identify vulnerabilities, develop proof-of-concept exploits, perform threat modeling and security reviews, and design mitigations such as hardware CFI, pointer masking, and memory tagging. Partner with architecture, hardware, and software teams to improve product security and drive adoption of secure development practices and verification technologies.

Lead design, automation, and operation of a scalable, secure Linux platform across physical, virtual, and cloud environments. Build IaC, provisioning, patching, security hardening, and lifecycle automation. Deploy and operate cloud infrastructure, integrate hybrid environments, and collaborate with engineering teams to improve platform reliability and maintainability.

Manage strategic state and local government accounts for NVIDIA’s AI and accelerated computing solutions. Own the full technology sales cycle, develop territory and account plans, build executive and technical relationships, collaborate with solution architects and channel partners, navigate public-sector procurement, forecast revenue, and achieve sales quotas. The role requires consultative selling to government organizations and travel of at least 25%.

Leads multifunctional initiatives defining safety architectures and requirements for autonomous vehicles. Develops safety concepts and analysis supporting continuous software delivery, improves safety metrics and analysis tools, evaluates safety data, and communicates readiness results. Collaborates with perception, AI, motion planning, and architecture experts to ensure DRIVE products meet rigorous safety standards.

Develop and lead production software-defined networking for NVIDIA’s global GPU cloud infrastructure. Design multi-tenant control and data planes using Open vSwitch, OVN, OpenFlow, Kubernetes, C, and Go. Build networking services, plugins, automation, testing, observability, and reliability improvements. Lead architecture and code reviews, mentor engineers, support on-call operations, and resolve complex production incidents through diagnostics and source-level debugging.

The Senior Production Engineer will scale AI infrastructure, manage production systems, implement monitoring capabilities, and ensure reliability and performance across NVIDIA's AI clusters.

Lead founding AI Safety & Security Engineering team, define harness architecture and engineering standards, drive Find/Validate/Patch roadmap, mentor engineers, and translate research into production-grade, secure ML systems.

Develop and formalize methods to validate reported vulnerabilities and generate/verify safe patches for internal NVIDIA targets. Define correctness, regression, and revalidation standards; produce repeatable, auditable processes and evidence. Apply AI-assisted workflows cautiously, perform bounded applied research on vulnerability classes, and document findings for independent security review.

Develops strategic relationships and revenue growth with universities and higher-education research institutions. Owns the complete sales cycle, from prospecting and discovery through negotiation and closing, while meeting quotas and forecasting revenue. Creates territory and account plans, translates complex software and computing requirements into NVIDIA solutions, and collaborates with solution architects, product teams, developer relations, business units, and channel partners. Requires consultative technology sales expertise and understanding of AI, accelerated computing, and research environments.

Design, develop, test, and extend NVIDIA’s large-scale object storage platform. Responsibilities include improving availability, reliability, durability, fault tolerance, and performance across deployments exceeding 10,000 nodes and exabytes of data. The role also automates storage infrastructure provisioning, management, and monitoring; supports AI/ML research teams; owns product delivery through support; and contributes to open-source storage projects.

Sell NVIDIA's networking portfolio to enterprise accounts, driving quota attainment by identifying, qualifying, and closing opportunities. Lead customer conversations across business and technical stakeholders, collaborate with solution architects and partners, and support solution development for AI and data center initiatives. Maintain pipeline, forecasting, and opportunity tracking in Salesforce while coordinating complex sales motions and building strategic customer relationships across Physical AI and Financial Services industries.

Deploy, manage, validate, and optimize large-scale AI compute and HPC infrastructure in Linux environments. Serve as a technical liaison among NVIDIA, partners, and enterprise customers; lead planning through implementation, document handoffs, transfer knowledge, troubleshoot hardware and software, and provide feedback for product and architecture improvements. The role involves networking, system design, automation, benchmarking, cluster provisioning, and customer-site travel up to 30%.

Own NVIDIA’s config-as-code foundation for its EDA compute farm. Design LSF deployment schemas, build federated deployment pipelines with staged rollout and rollback, eliminate configuration drift, and create regression testing for scheduled LSF upgrades. Partner with an LSF specialist to encode scheduler expertise into templates and policies. The role also requires infrastructure automation, GitOps at scale, tooling development in Go, Python, and shell, and management of stateful production infrastructure.

Lead cross-stack adoption of modern toolchains, build and code-health practices, and performance workflows on NVIDIA CPU platforms. Integrate and validate compilers, linkers, cross-compilation, and CI; profile and optimize large codebases; build automation and playbooks; drive integration blockers to owners and communicate measurable before-and-after results to engineering teams and leadership.

Lead invention of AI-driven ASIC development methodology, identify cross-stage bottlenecks, build scalable data pipelines, define metrics, mentor engineers, and evaluate AI/EDA research to improve predictability and cycle time.

Lead performance practices for large-scale AI systems, enhance datacenter products, and resolve complex performance issues through collaboration and technical expertise.

The Senior HPC Architect role involves deploying large-scale GPU compute clusters, optimizing system administration, and collaborating with researchers on HPC and AI solutions.

Design and implement high-performance, scalable storage systems and client libraries for AI workloads. Build data loading, checkpointing, caching, POSIX-style and object-store integrations, observability and telemetry, and validate performance with platform, SRE, and AI teams using modern engineering practices.

Translate cutting-edge agent research into secure, production-grade runtime systems: prototype, benchmark, reproduce methods, build agent harnesses and evaluation/red-team workflows, secure agent toolchains, and partner across research, product, and engineering to integrate features into OpenShell.

As a Principal Software Engineer, you'll develop software systems for NVIDIA's rack-scale infrastructure, defining software architecture, collaborating across teams, mentoring engineers, and ensuring high-quality technical decisions in complex environments.