Top Tech Jobs & Startup Jobs in Los Angeles, CA

Lead design and implementation of security systems and controls for large-scale AI and HPC cluster infrastructure. Drive incident response, risk assessment, system hardening, governance, audit readiness, and cross-team collaboration to protect hardware, software, and datacenter platforms.

Build AI-driven compiler intelligence for production compiler pipelines. Design compiler optimization workflows, develop learning-based decision systems, integrate LLMs with compiler infrastructure, and validate performance across workloads. Collaborate with compiler, architecture, and performance teams to deploy reliable, scalable solutions that improve runtime, compile time, and efficiency.

Design and optimize power-efficient ASIC, GPU, and processor hardware for mobile, embedded, and datacenter platforms. Develop power metrics, drive power reductions, and deliver verified RTL meeting performance, area, and power targets. Collaborate with architects, designers, verification engineers, and VLSI teams on high-performance designs.

Define high-level SoC subsystem and I/O architecture for LPU products, translate product requirements into architecture and IP specifications, build and validate functional/architectural models (C++, SystemC, Python), and drive tradeoffs across performance, power, reliability, and security while coordinating with IP, firmware, software, RTL, verification, and post-silicon teams.

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.

Lead hardware-software co-design for LLM inference: drive and document architecture, build executable C++ hardware models, optimize performance with good algorithms and parallelism, diagnose cross-team chip and subsystem issues, and automate workflows to improve efficiency.

Drive developer enablement for CUDA-Q by creating docs, examples, tooling, MCP servers, Agent Skills, prompt templates, and benchmarks. Analyze developer and agent workflows, define documentation and agent-consumable standards, run evaluations and metrics, and translate research into practical guidance to improve developer time-to-value for quantum and GPU-accelerated applications.

Design and build real-time, physics-informed AI models and synthetic data pipelines for quantum calibration and decoding. Develop surrogate models and GPU-accelerated implementations, apply reinforcement and online learning for calibration policies, co-design low-latency calibration-decoding systems, and collaborate across engineering and research to enable fault-tolerant quantum hardware.

Lead a data science team to design, build, and deploy large-scale, real-time AI/ML solutions (forecasting, diagnostics, LLM chatbot, retention models, optimization) to optimize GPU cloud gaming performance and user experience.

Serve as technical lead between NVIDIA and hyperscale CSPs on GPU firmware and system software. Drive firmware update orchestration, recovery procedures, multi-GPU coordination, telemetry/health monitoring, and incorporate CSP feedback into NVIDIAs roadmap to improve fleet-scale manageability and reliability.