Top Tech Jobs & Startup Jobs in Los Angeles, CA

Develop and deploy machine learning models, datasets, algorithms, and training recipes to improve AI safety for multimodal LLMs and agentic systems. Work across LLM security, frontier risks, agentic safety, multi-turn evaluation, content safety, hallucinations, and fairness. Apply post-training methods including SFT and RLHF/RLAIF, conduct safety evaluations and research, and collaborate cross-functionally with engineering, data science, and research teams.

Leads strategy and execution for reliable, scalable, and modern EDA compute infrastructure supporting chip development and tapeout. Coordinates global engineering programs, customers, vendors, and cloud and software tooling partners. Responsibilities include planning, forecasting, dependency management, agile guidance, metrics, reporting, issue resolution, technical discussions, process improvement, and senior-management communication.

Build and deploy AI/ML tools for GeForce NOW SRE operations, transforming production data, metrics, logs, and signals into incident root-cause analysis and operational forecasts. Lead LLM- and agent-based systems, develop large-scale data pipelines, optimize LLM workflows, and recommend sustainable AI platforms and architectures. The role also involves automation, Kubernetes, AWS cloud environments, monitoring, visualization, and production SRE practices.

Design and scale Kubernetes-native, GPU-accelerated cloud architectures for large-scale robotics simulation, synthetic data pipelines, training, and inference. Advise partners, optimize scheduling, storage, networking, and GPU utilization, and drive adoption of NVIDIA Physical AI frameworks while collaborating with product and engineering teams.

Lead HBM and LPDDR system integration and bringup for next-generation SoCs. Own memory performance, power, thermal, and reliability closure across silicon, package, board, and firmware. Drive post-silicon margining, VF shmoo, eye characterization, and correlation. Debug training, calibration, SI/PI, and system stability issues. Define validation, characterization, and issue-tracking plans to produce production-ready operating points.

Partner with industry and account teams to design and deliver NVIDIA-based AI, HPC, and GPU/networking solutions for industrial robotics. Engage customers and partners, produce technical documentation and samples, support deployments both in datacenters and at the edge, and lead technical engagements with lighthouse customers and solution partners.

Design and optimize high-performance C++/CUDA libraries for GPU-based data processing. Improve multi-node GPU communication (UcxExchange), optimize Presto GPU query performance, and lead enhancements across Presto, Velox, and cuDF projects for efficient DataFrame and database acceleration.

Design and optimize high-speed, high-density ASIC package layouts and substrate breakouts. Perform pinout optimization, routing, placement, stack-up, power distribution, CAD library development, feasibility studies, and productivity methodology improvements while collaborating with package leads and cross-functional teams.

Design and implement lane-level localization, perception-map association, and lane selection systems using navigation maps. Develop efficient, safe C++ algorithms and productize software to automotive quality and safety standards for deployment in consumer autonomous vehicles. Work with large-scale real and synthetic datasets and collaborate across teams.

Design, develop, and operate large-scale SDN control and data plane software (OVS/OVN/OpenFlow) for NVIDIA AI Cloud. Build network orchestration and IaC (gRPC/REST, Ansible, Terraform, ArgoCD/Flux), maintain CI/CD pipelines, implement observability/monitoring, drive upstream open-source contributions, and collaborate with SRE/DevOps to ensure production reliability and performance SLAs.