Top Tech Jobs & Startup Jobs in Los Angeles, CA

Design, build, deploy, and operate large-scale GPU cloud infrastructure and tooling for AI training and inference. Perform performance analysis, capacity management, monitoring, automation, incident response, and lifecycle support for distributed multi-GPU/multi-node systems.

Design and implement high-performance, low-power CPU microarchitecture and RTL. Coordinate with verification and physical design teams to meet performance, timing, and power targets. Support chip floorplanning, power/clock distribution, timing closure, and back-end verification. Develop flows and scripts to aid design activities.

Design and build PyTorch components and production AI solutions optimized for supercomputers with thousands of GPUs. Collaborate with NVIDIA hardware/software teams, internal researchers, and the PyTorch community to improve GPU performance, distributed training, and AI tooling.

Lead strategic engagement in the U.S. Federal software ecosystem, collaborating with ISVs to accelerate NVIDIA AI platform adoption and architect critical software solutions for defense and public sector.

Lead product strategy and multi-year cloud deployment roadmaps for Omniverse. Engage partners and customers, gather requirements, prioritize backlogs, measure adoption and usage metrics, drive cloud integrations and GPU-accelerated solutions, and coordinate go-to-market and executive communications to grow developer and partner adoption.

The Senior Product Manager will lead strategic go-to-market plans for NVIDIA's CUDA-X libraries, collaborating across teams to drive execution and growth in scientific computing markets.

The role involves owning physics models, defining manufacturing specifications, and validating designs to ensure product quality and performance. The architect will utilize first-principles thinking and AI to improve workflows and drive alignment across engineering teams.

The Developer Experience Manager will enhance developer journeys by defining AX standards, analyzing needs, evaluating tools, and promoting effective content use for developers and AI agents.

Lead a team to build and operate DGX Cloud infrastructure, focusing on Kubernetes operations, automation, and reliability. Manage production systems and engineer practices for cloud infrastructure.

The role involves analyzing deep learning networks, optimizing compiler algorithms, and collaborating across teams to enhance deep learning software performance and usability.