Top Tech Jobs & Startup Jobs in Los Angeles, CA

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.

Architect, build, and deploy LLM-powered AI systems and automation to accelerate post-silicon validation and toolchain workflows; integrate AI across engineering teams, evaluate emerging frameworks, measure impact, and operationalize solutions from prototype to production while supporting silicon bring-up and lab debug.

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 and optimize agentic AI systems for NVIDIA’s CUDA ecosystem, including agent architectures, multi-agent workflows, tool use, memory, orchestration, training, verification, reward, and evaluation systems. Co-design AI systems across models, inference, compilers, runtimes, libraries, kernels, and GPUs. The role requires strong C/C++, Rust, and Python skills, GPU programming expertise, and experience with agent systems, reinforcement learning, or modern AI inference.

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.

Design, develop, test, and optimize system software for next-generation ARM-based SoCs across pre- and post-silicon phases. Analyze architectural bottlenecks, workload performance, and performance-per-watt tradeoffs; develop hardware/software policies and optimization strategies. Lead performance analysis, competitive benchmarking, architecture documentation, and adoption of improvements across NVIDIA software products and open-source SDKs.

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.

Lead research, architecture, and production development of hardware formal verification tools enhanced by agentic AI. Build formal verification algorithms, multi-agent systems, solver orchestration, RTL analysis, automated SystemVerilog Assertion generation, and high-performance C/C++ implementations for commercial EDA suites. The role requires deep expertise in formal methods, hardware verification, AI frameworks, RTL languages, and 15+ years developing advanced EDA tools.

Define system and technical requirements for fault-tolerant quantum computing across hardware, software, and firmware. Develop real-time quantum error correction and calibration approaches, perform systems analysis across qubit modalities, and create and review test cases. Collaborate with product, research, engineering, and external partner teams to advance quantum control systems, quantum computing products, and related NVIDIA technologies.

Develop optimized GPU algorithms and high-performance machine learning solutions for vector search, databases, and data processing. Responsibilities include designing, implementing, benchmarking, debugging, and optimizing C++, CUDA, and Python libraries; developing clustering and visualization algorithms; collaborating cross-functionally; and contributing to open-source projects such as cuML, cuVS, and RAFT.