Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

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

Lead the design and implementation of a GPU-accelerated propagation engine for predicting radio signal travel in 3D environments. Focus on real-time ray-tracing for 5G and 6G network simulation, optimizing for effective channel characterizations and rapid updates.

Design and develop scalable infrastructure for deep learning libraries, automate build/test processes, and contribute to open-source tools.

The Senior Solutions Architect will lead software development, optimize CI/CD systems, develop cloud infrastructure solutions, and collaborate across NVIDIA teams.

Design and implement high-performance communication protocols and algorithms for NVIDIA networked supercomputers and datacenters. Develop production-grade communication frameworks and applications, optimize performance and scalability, and collaborate with networking chip design teams on hardware/software co-design.

Lead functional safety analysis for autonomous vehicle compute and communications platforms. Perform fault-tree and model-based analyses, derive diagnostic measures, develop automation for multi-layer system analysis, interpret safety documentation, and integrate system/software/hardware safety methodologies to meet hardware safety metrics.

The role involves performing data analysis for datacenter applications, using machine learning for GPU systems, and providing insights on trends to enhance workflows.

The role involves developing an inference framework for large language models and optimizing performance on embedded platforms, collaborating across teams and contributing to CUDA kernel development.

Lead technical engagements with cloud partners to design, integrate, and deploy large-scale GPU AI/HPC infrastructure. Drive proof-of-concepts, production delivery, performance tuning, and adoption of deep learning frameworks, models, and NVIDIA software across the customer lifecycle, while collaborating cross-functionally and presenting technical content.

Serve as the embedded systems expert for NVIDIA Physical AI partners, integrating sensors, deploying and optimizing robotics foundation models on Jetson-class edge hardware, guiding customers from prototype to production, and delivering reference implementations and workshops.