Overview As Principal SoC Architect, you will own the architectural definition of next gen SoCs that fuse GPUs, vision accelerators, and real-time processors for edge AI, robotics, and autonomous driving. You will lead cross functional work across robotics, automotive safety, and silicon design to drive end to end architecture and ecosystem enablement. Expect to model performance, power, and area, validate real time safety targets, and support post silicon production for tier 1 customers. This role offers a chance to shape silicon fabric and system level integration at scale within NVIDIA's automotive and robotics initiatives.
Compensation / Benefits- equity
- benefits
- base salary (range provided)
- location Santa Clara (US)
- career growth opportunities
Responsibilities- End-to-End SoC lifecycle ownership from concept to bring-up and ecosystem enablement
- Co-design of hardware features with software, DL, and safety teams for low-latency robotics and autonomous driving pipelines
- PPA modeling and analysis focused on thermally constrained enclosures and ECUs
- Specification and modeling to validate architectural choices
- Architectural validation plans ensuring real-time execution and safety metrics
- Post-silicon and production support including silicon debugging, performance tuning, and customer documentation for robotics/automotive clients
Key requirements- 15+ years of deep architecture design experience in high-performance silicon
- Meaningful industry expertise in top-level SoC definition
- Practical knowledge of high-speed interfaces (PCIe, GMSL/Camera interfaces, TSN)
- Experience with multimedia/vision accelerator pipelines, CPU/GPU cache coherency, virtualization, and hardware security
- Deep understanding of hardware support for RTOS, deterministic latency, and mixed-criticality workloads
- Strong cross-functional technical leadership and communication across micro-architecture to software layers
- Master's or PhD in Computer Engineering, Electrical Engineering, or equivalent experience
- Cross-functional collaboration
- clear communication and negotiation across teams
- problem solving across abstraction levels
- SystemC, C++, Python (for architectural simulation and modeling)
- PCIe, GMSL, Camera interfaces, TSN
- Multimedia/vision accelerator pipelines, cache coherency between CPU/GPU
