Top Tech Jobs & Startup Jobs

The role involves developing high-speed interfaces and analog circuits, conducting schematic designs, defining circuit requirements, and supporting post-silicon debugging. The engineer will collaborate with layout engineers and utilize design tools to ensure system performance.

As a Senior Linux Systems Engineer at NVIDIA, you will work on Linux security, containerization of high performance computing software, and enhance management software. You'll refine requirements, design algorithms, implement solutions, and address complex technical issues across teams. Open Source contributions are a plus.

The Senior SoC Power Architect at NVIDIA will optimize power and performance for various SoCs, work collaboratively across teams to enhance power solutions, and create power models for evaluating architecture in different workloads. The role emphasizes understanding power efficiency factors at multiple levels and requires strong teamwork skills.

The Senior Performance Engineer will lead the implementation of performance practices in large-scale AI systems and datacenter products. Responsibilities include architecting performance design, collaborating with internal teams for improvements, and troubleshooting firmware and software issues to enhance GPU computing performance.

The Technical Marketing Engineer will create and disseminate technical content to promote NVIDIA's accelerated CAE and EDA solutions. Responsibilities include collaborating on product how-tos, delivering presentations, inspiring developers, and generating training materials. Successful candidates will possess strong technical and communication skills, alongside a background in software development or technical marketing.

As a Senior GPU Architect, you will design GPU profiling features, build performance models, create validation test plans, and innovate hardware profiling methods. Collaboration with teams globally is key to ensuring performance optimization in GPUs.

The Senior HPC Architect role involves deploying and managing large-scale GPU compute clusters, providing engineering solutions for GPU computing products, and collaborating with researchers and developers. Responsibilities include system administration, large-scale performance architecture, and fostering technical relationships within the engineering community.