Top Tech Jobs & Startup Jobs

The Software Tools Automation Engineer at NVIDIA will develop and maintain software tools, scripts, and frameworks to streamline engineering processes. Responsibilities include improving software architectures, collaborating with cross-functional teams, and providing support through bug fixes and documentation. Prospective candidates should have significant experience in automation testing and scripting, and a strong foundation in software development practices.

The CES Software Architect will design and implement a scalable fraud prevention and account protection service. Responsibilities include creating advanced algorithms for fraud detection, developing APIs, ensuring compliance with security standards, and mentoring teams. The role demands expertise in security-focused services and cloud architecture.

The role involves architecting and implementing silicon debug capabilities for NVIDIA's GPUs, identifying and resolving inefficiencies, collaborating with various teams, training junior engineers, and verifying hardware at the full-chip level.

Lead board/system SI design activities, system-level signal integrity simulation, optimize Power delivery network on PCBs, work with Application Engineering, conduct TDR & VNA measurements, ensure high-speed interface designs meet industry standards and requirements.

As a Senior ASIC Timing Engineer at NVIDIA, you will drive timing analysis and closure for GPUs, CPUs, DPUs, and SoCs. This includes working on timing constraints, improving timing flows, and collaborating with various teams to ensure timing and power convergence. You will also analyze timing paths and apply your expertise to ensure successful implementation of ECOs.

The Senior High-Performance LLM Training Engineer will optimize LLM training workloads, analyze performance across GPU architectures, implement production-quality software, and help shape NVIDIA’s hardware roadmaps. Responsibilities include profiling AI training workloads, contributing to MLPerf benchmarks, and creating automation tools for workload analysis and optimization.

The Senior High-Performance AI Training Engineer will analyze, profile, and optimize AI training workloads on advanced hardware, particularly focusing on GPU performance. This role involves implementing production-quality software across NVIDIA's deep learning stack, building tools for automation, and contributing to the MLPerf benchmark suite. Candidates must have a strong background in deep learning and experience in optimizing application performance on GPUs.