Top Tech Jobs & Startup Jobs in Los Angeles, CA

The Senior Production Engineer will scale AI infrastructure, manage production systems, implement monitoring capabilities, and ensure reliability and performance across NVIDIA's AI clusters.

The role involves architecting and operating NVIDIA's cloud-native attestation platform, developing high-availability services, collaborating with cross-functional teams, and mentoring engineers.

The role involves developing an inference framework for large language models and optimizing performance on embedded platforms, collaborating across teams and contributing to CUDA kernel development.

Lead technical engagements with cloud partners to design, integrate, and deploy large-scale GPU AI/HPC infrastructure. Drive proof-of-concepts, production delivery, performance tuning, and adoption of deep learning frameworks, models, and NVIDIA software across the customer lifecycle, while collaborating cross-functionally and presenting technical content.

Serve as the embedded systems expert for NVIDIA Physical AI partners, integrating sensors, deploying and optimizing robotics foundation models on Jetson-class edge hardware, guiding customers from prototype to production, and delivering reference implementations and workshops.

The Senior HPC Architect role involves deploying large-scale GPU compute clusters, optimizing system administration, and collaborating with researchers on HPC and AI solutions.

Design and implement high-performance, scalable storage systems and client libraries for AI workloads. Build data loading, checkpointing, caching, POSIX-style and object-store integrations, observability and telemetry, and validate performance with platform, SRE, and AI teams using modern engineering practices.

Lead GPU and HPC cluster architecture and deployment for cloud partners: design end-to-end GPU/NVLink infrastructures, perform performance modeling, validate and debug cluster configurations, support NPI deployments, and serve as technical liaison between engineering, product, and field teams.

Lead long-term strategy and technical direction for GPU memory, on-chip interconnect, and architectural simulation. Define modeling methodology, validation, workloads, and AI-assisted model generation. Identify bottlenecks, recommend architectural changes, coordinate cross-team efforts, and mentor senior engineers to influence future GPU product decisions.

Design and simulate analog/digital circuits and power delivery networks (die to platform) for processors. Perform block- and system-level simulations, ensure reliability/performance, mentor junior engineers, and collaborate globally to improve netlist and timing quality.