Top Tech Jobs & Startup Jobs

Lead partner engagements to design, prototype, and deploy production-grade agentic AI systems on NVIDIA GPUs. Architect multi-agent workflows, RAG, tool use, planning, memory, evaluation, and guardrails; build PoCs, benchmarks, and reference architectures; optimize performance and cost; guide model customization and post-training workflows; use agent harnesses and translate findings to product and engineering teams for platform improvement and field enablement.

Design hardware accelerator and processor architectures for next-generation AI systems. Collaborate with DL researchers, hardware architects, and software engineers to co-design, prototype, and benchmark systems. Analyze DL workloads, identify bottlenecks, propose optimizations, implement prototypes, and validate performance improvements.

Lead design and implementation of GPU-accelerated libraries and integrations for Apache Spark. Develop Java/Scala and CUDA/C++ components for I/O and DataFrame operations, enable interoperability with table formats and metastores, contribute to open source projects, collaborate on distributed systems at scale, and optimize cross-platform CUDA/C++ libraries and CI/testing infrastructure.

Lead signal and power integrity analysis for high-speed systems: develop SI solutions, run 3D/2.5D/2D EM and system-level simulations, correlate models with lab measurements, create board/substrate SI guidelines, automate simulations and data visualization, and collaborate across package/PCB/ASIC design teams.

Lead research and development of algorithms and systems for robotic manipulation and loco-manipulation; integrate methods into real robot systems; co-lead multi-person projects; publish and engage with the academic community; transfer research into NVIDIA products; and mentor interns and junior researchers/engineers.

Develop and validate SoC and GPU boot and security firmware across automotive, embedded, and data-center platforms. Participate in pre-silicon simulation to silicon bring-up, debug boot stack issues, and collaborate with architecture, software, and hardware teams to ship next-generation NVIDIA SoCs.

Develop and verify CPU SoC boot firmware for pre- and post-silicon platforms. Define and decompose functional and safety requirements, perform failure analysis (FMEA/DFA), implement secure boot features, collaborate across teams, and support silicon validation and productization.

Lead pre-silicon system software bring-up and validation on simulation platforms. Develop automation, tools, and workflows to improve simulation-based development, debug complex cross-stack issues, enable teams to use virtual platforms, and drive platform readiness for new chips in early-development environments.

As a GPU Verification Engineer, you will verify ASIC designs of NVIDIA GPUs, define verification scope, develop test plans, and collaborate with teams.

Lead developer and partner adoption of NVIDIA Cosmos 3 and related world foundation models across robotics. Advise engineering teams, drive ecosystem engagement, support product launches, accelerate partner workloads, and provide product feedback to inform roadmap and research priorities.