Top Tech Jobs & Startup Jobs in Los Angeles, CA

Investigate and resolve escalated infrastructure issues across Linux, hardware, networking, Docker, GPUs, CUDA, and virtualization environments. Manage supplier onboarding, troubleshoot GPU workloads and performance problems, support L1 overflow, create diagnostic automation with Python and Bash, and maintain runbooks and escalation documentation. Collaborate with engineering and support teams to address systemic infrastructure issues and communicate solutions clearly.

Develop and extend a GPU cloud daemon that orchestrates hosts across a large fleet. Improve infrastructure performance, reliability, monitoring, telemetry, and containerization. Design market-based resource management systems, harden code and infrastructure to zero-trust standards, and benchmark and eliminate bottlenecks across hypervisor, container, and network layers.

Design and optimize GPU kernels and tensor libraries for scalable AI inference. Apply HPC and parallel-computing techniques, evaluate emerging GPU architectures and resource-management approaches, and improve GPU infrastructure efficiency. The role requires advanced C++ development, parallel programming expertise, systems optimization, and performance tooling experience. This is a full-time, on-site position in San Francisco or Los Angeles.