Top Tech Jobs & Startup Jobs in Los Angeles, CA

Design, integrate, and deploy large-scale AI/HPC GPU infrastructure with NVIDIA Cloud Partners. Drive technical engagements across the customer lifecycle, build PoCs, troubleshoot performance and scaling, and deliver technical content and workshops.

Lead and coach a storage production engineering team to design, deploy, and operate large-scale storage systems. Own capacity planning, lifecycle management, HA/disaster recovery, automation, monitoring, incident response, and partnerships with engineering and AI teams to improve data pipelines and performance.

Lead and grow an engineering team building GPU‑accelerated deep learning inference frameworks. Drive roadmap, collaborate with compiler/libraries/research teams, optimize LLM and multimodal model performance, and oversee multi‑GPU communications and production deployment of inference software.

Recruit, engage, and accelerate Public Sector, Energy, and CAE startups into the NVIDIA Inception program. Drive technical adoption, co-selling, and go-to-market initiatives with cross-functional teams, partners, VCs, and government agencies. Track metrics, perform market analysis, and support startups from onboarding through early adoption and scaling.

Lead technical engagement for AI training and infrastructure at scale. Collaborate with engineering teams and customers to ensure successful deployment and optimization of AI/ML solutions.

Design and validate embedded SRAM macros at transistor level, supervise layout and verification, develop/automate SRAM compiler flows, explore advanced process-node techniques for optimal PPA, and collaborate with SoC, test, and productization teams to deliver production silicon IP.

Build and operate massively distributed, scalable GPU cluster platforms (DGX Cloud) to monitor, diagnose, and remediate GPU performance issues. Ensure reliable, high-performance production AI clusters, evaluate failures, improve services via incident management, and collaborate across teams to automate cluster operations and scheduling.

Lead architecture and delivery of an ML infrastructure efficiency platform across silicon co-design teams. Define platform contracts, onboarding, orchestration, auth, observability, storage/caching, and SLA enforcement. Own production operation, security, reliability, and performance while mentoring engineers and driving cross-team technical decisions.

The role involves mentoring on Gen AI solutions, developing POCs, educating customers on technologies, and collaborating with various teams for product development.

Build and maintain automation flows and methodologies for VLSI interposer design. Develop tools and applications (Python/C++) to construct, analyze, and validate interposer designs, improve designer workflows, and integrate AI/ML-assisted techniques into EDA environments.