Top Tech Jobs & Startup Jobs in Los Angeles, CA

Serve as the embedded systems expert for NVIDIA Physical AI partners, integrating sensors, deploying and optimizing robotics foundation models on Jetson-class edge hardware, guiding customers from prototype to production, and delivering reference implementations and workshops.

Design and implement CUDA Tile compiler transformations, MLIR dialects, lowering passes, and optimization techniques for NVIDIA GPUs. Optimize tile-based kernel performance across GPU generations, define public APIs, conduct performance analysis, and develop robust software, tests, and debugging workflows. The role requires independent project ownership and collaboration within a product-focused engineering team.

Lead technical engagements with cloud service providers on rack-scale system software and firmware. Drive architecture alignment, integration readiness, error handling and recovery, health telemetry, firmware orchestration, and serviceability. Capture CSP feedback, influence NVIDIA system software design, improve tooling and tests, and mitigate execution risks through early collaboration.

Design and implement high-performance communication protocols and algorithms for NVIDIA networked supercomputers and datacenters. Develop production-grade communication frameworks and applications, optimize performance and scalability, and collaborate with networking chip design teams on hardware/software co-design.

Design and implement high-performance, scalable storage systems and client libraries for AI workloads. Build data loading, checkpointing, caching, POSIX-style and object-store integrations, observability and telemetry, and validate performance with platform, SRE, and AI teams using modern engineering practices.

Develop and implement compiler optimization algorithms for deep learning workloads, analyze networks, debug and profile GPU performance (CUDA), define public APIs, and deliver ahead-of-time and just-in-time compilation techniques for NVIDIA GPUs to improve inference performance, build times, and memory efficiency.

Translate cutting-edge agent research into secure, production-grade runtime systems: prototype, benchmark, reproduce methods, build agent harnesses and evaluation/red-team workflows, secure agent toolchains, and partner across research, product, and engineering to integrate features into OpenShell.

Design and implement RTL and system-level SoC modules, perform logic synthesis and timing analysis, integrate modules into SOC, collaborate with architects and verification teams, support silicon bring-up, and improve design flows and methodologies to enhance efficiency and chip yield.

Architect and demonstrate simulation workflows using DSX Sim and Omniverse libraries to help partners and customers build, validate, optimize, and operationalize AI factory digital twins. Drive integration of Omniverse libraries, develop reference architectures, prototypes, benchmarks, and sample workflows, and coordinate with sales, product engineering, and partners to resolve blockers and advance adoption.

Lead cross-stack adoption of modern toolchains, build and code-health practices, and performance workflows on NVIDIA CPU platforms. Integrate and validate compilers, linkers, cross-compilation, and CI; profile and optimize large codebases; build automation and playbooks; drive integration blockers to owners and communicate measurable before-and-after results to engineering teams and leadership.