Jobs at NVIDIA

Develop and maintain hardware abstraction layers, core system libraries, drivers, and runtimes; improve reliability via automation and diagnostics; debug multi-component system issues; support hardware bring-up and NPI; collaborate with hardware, compiler, and operations teams; contribute to documentation and tooling.

Lead deep-learning inference optimization for edge/autonomous systems: analyze models to operator/kernel level, benchmark and deploy TensorRT/compiler solutions on Jetson/DRIVE/ARM/GPU platforms, collaborate with compiler/runtime/hardware teams, and engage partners to deliver production-ready performance improvements.

Lead the strategy and evolution of internal hardware infrastructure tools used in ASIC development, optimize workflows, and drive cross-functional alignment to enhance engineering productivity.

The role involves developing AI and ML applications to enhance chip design, collaborating with hardware teams, and creating innovative tools for productivity.

Develop an AI Platform for efficient training and inference of large scale models, focusing on scheduling and resource management.

The role involves building AI inference systems, optimizing GPU performance, and developing benchmarking methodologies for large-scale deployments.

The role involves developing verification infrastructure, executing test plans, ensuring code coverage, and collaborating with design teams for post-silicon verification.

The Solutions Architect for AI Infrastructure at NVIDIA will define, deploy, and manage large-scale GPU systems, providing technical support and guidance to customers throughout the entire project lifecycle.

As a Networking Solutions Architect at NVIDIA, you will design and deploy AI infrastructure, optimize solutions, and collaborate with partners on high-performance networking.

As a Senior Software Engineer, you'll work with large-scale LLM serving, improve performance on NVIDIA's inference stack, and collaborate with customers on benchmarking and optimization.

The Senior ASIC Verification Engineer will verify high-speed coherent interconnect designs, develop verification infrastructure, and ensure correctness of the designs while collaborating with various teams.

The engineer will develop algorithms and optimizations for NVIDIA's LPX inference stack, focusing on compiler components, performance metrics, and collaboration with hardware teams.

The role involves developing algorithms for inference optimization, building compiler components, and collaborating across teams to enhance performance on NVIDIA platforms.

The Developer Relations Manager will build partnerships to support AI solutions, provide technical advisory, and collaborate with internal teams to enhance adoption of NVIDIA technologies.

Develop algorithms and optimizations for LPX inference and compiler stack, focusing on deep learning and performance enhancements across NVIDIA systems.

You will verify ASIC design implementation, develop verification infrastructure, optimize verification flows, and collaborate with teams on advanced methodologies.

Drive AI-enabled ASIC development methodology by identifying cross-stage bottlenecks, building data pipelines and metrics, creating automation and AI models, mentoring engineers, and evaluating advances in AI and EDA to improve predictability, convergence, and cycle time.

Manage sales and partnerships with Canadian higher education institutions, focusing on High-Performance Computing and AI solutions, driving revenue growth and strategic initiatives.

As a Senior ASIC Design Engineer, you'll implement high-performance RTL, analyze architectural trade-offs, and collaborate across teams to deliver cutting-edge designs.

As a Senior Formal Verification Engineer, you will verify ASICs using formal methods, collaborate multi-functionally, lead methodology enhancements, and mentor junior engineers while ensuring compliance and correctness.