Top Tech Jobs & Startup Jobs in Los Angeles, CA

Architect and optimize large-scale GPU AI infrastructure: profile distributed training/inference, diagnose networking and system bottlenecks, design high-performance clusters, lead POCs, automate benchmarking, and drive technical engagements with customers and internal teams.

Lead founding AI Safety & Security Engineering team, define harness architecture and engineering standards, drive Find/Validate/Patch roadmap, mentor engineers, and translate research into production-grade, secure ML systems.

Develop and advance multimodal agentic AI systems using deep learning, reinforcement learning, large language models, and audio-visual reasoning. Responsibilities include training and deploying foundation models, improving post-training and alignment methods, developing planning and tool-use capabilities, managing multimodal datasets and evaluation pipelines, and leading research on embodied AI, voice interaction, and long-horizon task completion.

Develop and formalize methods to validate reported vulnerabilities and generate/verify safe patches for internal NVIDIA targets. Define correctness, regression, and revalidation standards; produce repeatable, auditable processes and evidence. Apply AI-assisted workflows cautiously, perform bounded applied research on vulnerability classes, and document findings for independent security review.

Design, develop, and optimize system software and firmware for SoC-based O-RAN infrastructure. Implement power-management policies (DVFS, clock/power gating, thermal control), analyze RU/DU workloads, build performance and power models, create measurement and test tooling, validate on simulation/emulation and silicon, and influence SoC and platform architectures for 5G/6G deployments.

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.

Design, build, and operate core cloud-native infrastructure services for NVIDIA DGX Cloud. Develop scalable, secure microservices and automation for provisioning and lifecycle management, integrate internal and external platforms, and implement observability and security to ensure reliable, global production operations.

Lead technical partnership with Alphabet teams to drive adoption and integration of NVIDIA libraries, models, and frameworks. Coordinate cross-functional engineering and GTM teams, resolve integration challenges, influence product roadmaps, and deliver joint solutions that accelerate partner workloads and developer adoption.