Top Tech Jobs & Startup Jobs

Lead technical engagement for AI training and infrastructure at scale. Collaborate with engineering teams and customers to ensure successful deployment and optimization of AI/ML solutions.

Design and implement NVLink protocol and GPU subsystem logic: micro-architecture, RTL implementation and debug, timing- and power-optimized logic design, collaborate with verification and physical design teams, support floorplan, power/clock distribution, timing closure, and back-end verification; develop supporting flows and tools.

Design and validate embedded SRAM macros at transistor level, supervise layout and verification, develop/automate SRAM compiler flows, explore advanced process-node techniques for optimal PPA, and collaborate with SoC, test, and productization teams to deliver production silicon IP.

Own post-sale relationships for federal customers, develop and execute Customer Success Plans, run executive reviews, drive adoption of NVIDIA AI solutions in classified/air-gapped environments, manage customer health and escalations, partner with integrators, provide product feedback, and ensure renewal readiness.

Lead end-to-end verification of Ethernet/InfiniBand NICs and switches: design test topologies, implement and mentor automation, execute regression/performance/functional/scale tests, generate reports, reproduce/debug complex customer issues, and drive product verification cycles.

Own and scale a multi-tenant CI-as-a-Service platform (GitLab CI and GitHub Actions) and Kubernetes substrate. Ensure reliability, autoscaling, SLO-driven capacity, observability, self-service pipelines, and developer experience across GPU/ARM/CPU build and test workloads.

Lead architecture and build AI-native developer tooling and autonomous agent systems to accelerate engineering workflows. Drive platform standards for reliability, safety, observability, and cost-efficiency while partnering across teams and mentoring senior engineers.

Lead GPU and NVLink-based cluster design and validation for large-scale AI and HPC deployments. Advise cloud partners on architectures, perform performance modeling, debug deployment issues, support NPI rollouts, and relay field feedback to engineering.

Develop and maintain simulation frameworks on NVIDIA Omniverse to train, evaluate, and benchmark robot foundation models; integrate LLM/agentic workflows; collaborate with researchers, write production-quality code, and participate in testing, CI, and deployment.

Develop system software components, collaborate on SOC designs, support DPU projects, optimize system-level resource utilization, and engage in all product development lifecycle stages.