Top Tech Jobs & Startup Jobs in Los Angeles, CA

Develop and optimize deep learning compiler infrastructure for high-performance inference across GPUs, data centers, devices, automotive, and robotics. Responsibilities include analyzing neural networks, creating compiler optimization algorithms, defining APIs, improving performance and memory efficiency, implementing compiler techniques, and collaborating with software framework and hardware architecture teams. The role also involves software design, debugging, performance analysis, testing, and independently leading development efforts.

Deploy, manage, validate, and optimize large-scale AI compute and HPC infrastructure in Linux environments. Serve as a technical liaison among NVIDIA, partners, and enterprise customers; lead planning through implementation, document handoffs, transfer knowledge, troubleshoot hardware and software, and provide feedback for product and architecture improvements. The role involves networking, system design, automation, benchmarking, cluster provisioning, and customer-site travel up to 30%.

Develop and optimize GPU-accelerated algorithms for quantum circuit simulations, collaborating with various teams, and leading technical efforts.

The Senior Formal Verification Engineer will verify sophisticated ASIC builds using formal methods, collaborate with architecture teams, develop verification environments, and support silicon debug.

The Senior LLVM Compiler Engineer will contribute to upstream LLVM development, lead design discussions, and ensure high-quality compiler solutions in collaboration with open-source communities.

Leads technical developer-relations strategy for NVIDIA platforms across capital markets. Advises quants, traders, developers, financial institutions, ISVs, and cloud providers; demonstrates CUDA, CUDA-X, AI frameworks, and accelerated computing solutions; supports partner onboarding and integrations; develops benchmarks, sample code, and reference implementations; gathers ecosystem feedback; influences product roadmaps; and represents NVIDIA at industry events, workshops, and conferences.

Build scalable tools and workflows for analyzing and optimizing AI training and inference performance. Integrate profiling infrastructure with AI frameworks, identify workload bottlenecks, automate diagnosis, and translate engineers’ needs into intuitive tooling. Collaborate with performance engineers, hardware architects, and software teams to align profiling capabilities with real-world workloads.

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.

Develop and optimize the open-source Triton compiler for high-performance AI workloads on NVIDIA GPUs. Design compiler technology using MLIR, generate efficient low-level GPU code, tune kernels with inline PTX, analyze hardware architectures, and optimize advanced AI algorithms and numerics. Collaborate with hardware architects and CUDA compiler teams while applying parallel programming, computer architecture, assembly, and performance debugging expertise.

Provide technical mentorship to customers adopting NVIDIA’s GenAI stack, build and deploy agentic AI solutions, create demonstrations and proofs of concept, deliver technical workshops, develop industry collateral, and collaborate with engineering, product, and sales teams to secure design wins. The role focuses on optimizing and deploying large language models, leveraging GPU clusters, inference engines, cloud platforms, and AI development frameworks.