Top Tech Jobs & Startup Jobs

As a Principal Engineer for AI Software Resiliency at NVIDIA, you will lead the engineering of resiliency features for AI supercomputers, focusing on reducing downtime, improving software quality, and integrating these features into frameworks like PyTorch and JAX/XLA. Your role involves collaboration across teams and with customers to ensure effective deployment and performance of AI resilience solutions.

As a Senior Software Architect at NVIDIA, you'll design and develop advanced solutions in network programmability, collaborate across teams, and drive proof-of-concept developments in areas like AI and deep learning. Your role involves researching and creating innovative architectural solutions for a modern data center environment.

The Senior System Software Engineer will work on integrating proximity sensing and positioning solutions for NVIDIA's automotive systems. Responsibilities include collaborating with global teams, developing software solutions, debugging sensor data pipelines, and evaluating vendor products for system integration.

As a Senior ASIC Design Engineer, you'll design and implement Memory Controllers for NVIDIA's GPUs and SoCs. Responsibilities include micro-architecture and design including RTL design, synthesis, verification, and timing analysis, working collaboratively with other engineers while leveraging groundbreaking CAD tools.

The Senior Software Engineer will develop and support NVIDIA's GPU administration tools, focusing on system and device monitoring for NVIDIA Tegra platforms. Responsibilities include coding and maintaining software for Compute GPU products on Windows and Linux, collaborating with cross-functional teams, and driving development efforts for new features and improvements.

As a Principal Graphics Hardware Architect at NVIDIA, you will design and enhance features in GPU architecture, collaborate with top architects to build simulators, and develop software for hardware testing. Your role includes creating test plans, validating performance models, and pushing the boundaries of graphics and computing capabilities.

Lead the design of GPU compute clusters for AI, HPC, and compute-intensive workloads. Optimize datacenter resource usage and drive operational excellence through automation. Collaborate with multi-functional teams to improve performance and cost-effectiveness of AI computing operations.