Jobs at NVIDIA

The Senior Solutions Architect will lead the integration of NVIDIA technology into HPC their environments, guiding customers through sales for GPU Computing products, while collaborating on deep learning and data analytics solutions.

Design and implement user-space applications and large-scale InfiniBand network simulators, optimize routing algorithms and performance for Docker and cloud deployments, and collaborate cross-functionally to add features and improvements.

Create OpenUSD-based scenes, demos, and reusable visualization workflows that combine CAD, simulation, and engineering data in NVIDIA Omniverse. Translate technical outputs into clear visual narratives, prototype demo content with engineering and product teams, and develop pipelines to preserve fidelity across geometry, time-varying, volumetric, and point-based data for developer and customer-facing experiences.

Perform physical mask/layout for mixed-signal and high-speed datapaths in advanced FinFET CMOS nodes using Cadence Virtuoso. Collaborate with mixed-signal designers on floorplanning, custom layout, DRC/LVS verification, and deck customization while iterating quickly in a team environment.

The Senior QA Software Engineer will test and validate virtual networking silicon and software, developing Python automation suites and collaborating with R&D for quality assurance.

Lead a team of ~5 engineers to design and implement advanced networking and distributed-computing solutions across application, OS, driver, firmware, and GPU/CUDA layers. Collaborate with chip architects, partners, and customers to deliver high-performance, production-ready technologies for AI, HPC, storage, cloud, SDN/NFV, and 5G.

The Senior System Software Engineer will develop software tools for provisioning NVIDIA chips, coordinate tool lifecycles, and collaborate with various teams.

Design and develop infrastructure libraries for ATE systems, enhance test program architecture, and collaborate cross-functionally to improve product quality and time-to-market.

Design and develop RDMA protocols for AI networking, collaborate with teams to innovate solutions, and build proofs-of-concept.

Develop algorithms and optimizations for inference and compiler stack, enhance performance metrics, collaborate with hardware teams, and publish work on novel approaches.

Develop and implement compiler optimization algorithms for deep learning workloads, analyze networks, debug and profile GPU performance (CUDA), define public APIs, and deliver ahead-of-time and just-in-time compilation techniques for NVIDIA GPUs to improve inference performance, build times, and memory efficiency.

Lead manufacturability and production readiness for thermal and mechanical components from NPI to mass production. Coordinate DFM, supplier qualification, tooling, processes, fixtures, testing, and automation. Identify and mitigate manufacturing risks, drive yield and quality improvements, and collaborate with R&D, operations, suppliers, and quality to ensure supplier readiness and scalable, cost-effective production.

Build an autonomous agentic platform to optimize AI models end-to-end (architecture, hyperparameters, GPU code). Develop agentic workflows, benchmarking for accuracy/latency/memory/throughput/cost, ensure reproducibility and safety, and lead technical initiatives while mentoring engineers across research, engineering, and product teams.

Lead modelling, analysis, and validation of GPU/SoC graphics and LPU features. Drive cmodel execution, infrastructure initiatives, tooling, test plans, coverage analysis, and cross-team collaboration to verify new architectures and features.

Verify high-performance, low-power security engines and RISC-V processor modules. Participate in micro-architecture development, author specifications, build SystemVerilog UVM verification environments, create verification and test plans to reach full coverage, debug RTL with designers, and deliver IP to cluster/FC verification and emulation.

Provide technical support to NVIDIA Enterprise customers by triaging and resolving issues, working with engineering on reproductions/logs, applying AI/ML and agentic AI to build support tools and products, documenting interactions and knowledge, and owning cases to resolution (occasional weekend/holiday support).

Design, build, extend, test, deploy, and maintain a centralized CI/CD infrastructure for open-source accelerated computing projects. Collaborate across teams, define CI/CD best practices, debug production issues, support other teams, and mentor junior engineers while setting technical direction and standards.

Design and implement RTL and system-level SoC modules, perform logic synthesis and timing analysis, integrate modules into SOC, collaborate with architects and verification teams, support silicon bring-up, and improve design flows and methodologies to enhance efficiency and chip yield.

The role involves deploying AI networking solutions in data centers, driving architectural decisions, troubleshooting network issues, and collaborating on customer projects for NVIDIA's technology solutions.

Design, build, extend, test, deploy, and maintain a centralized CI/CD infrastructure for open-source accelerated computing projects. Collaborate with teams, support platform users, ensure reliability/security/compliance, and debug production issues across the stack.