Top Tech Jobs & Startup Jobs in Los Angeles, CA

Develop and productize deep learning perception systems for autonomous driving, including traffic signal, sign, road marking, and construction object understanding. Lead end-to-end model development, data-driven improvement, simulation, augmentation, and deployment to embedded platforms. Optimize solutions for accuracy, safety, latency, robustness, and regional generalization while collaborating with data-labeling teams and contributing technical leadership.

Develop and scale simulation infrastructure for autonomous vehicle testing and validation across millions of virtual miles. Build metrics, test sets, and automation for KPI measurement, coverage, data quality, and performance. Collaborate with engineering, infrastructure, test, and release teams to resolve system-level issues and improve reliability. Mentor junior engineers and promote test-driven development. The role focuses on autonomous systems simulation, software engineering, data analysis, and large-scale validation.

Develop production-grade integrations for NVIDIA Grove across AI frameworks including Dynamo, llm-d, Ray, and PyTorch. Build adapters, plugins, operators, runtime components, reference workflows, and developer tooling. Optimize distributed multi-node and multi-GPU training and inference, improve Kubernetes observability, define APIs, and troubleshoot containers, networking, scheduling, CUDA, and runtime issues. Collaborate with engineering teams and open-source communities to upstream changes and maintain compatibility across evolving frameworks.

Lead cross-functional compiler software programs from concept to delivery, coordinating global teams, tracking risks and schedules, and improving development processes. Present status to executives, drive Agile and Waterfall projects, resolve technical/resource conflicts, and implement process and tool automation to ensure timely product releases.

Design, develop, integrate, test, and productize perception software for autonomous driving systems. Responsibilities include implementing robust and reusable software components, deploying deep neural network models to embedded real-time platforms, developing verification plans, debugging systems, maintaining documentation, and analyzing real or synthetic benchmark data. The role requires close collaboration with perception engineers and researchers throughout the software development lifecycle.

Design and build intelligent compiler systems, compiler-oriented agents, code transformation workflows, and numerical verification infrastructure. Develop systems for low-level IR reasoning, code generation, optimization, differential testing, regression detection, and correctness validation across GPU-centric workloads. Collaborate with compiler, CUDA, runtime, library, and hardware teams to integrate capabilities into NVIDIA products while optimizing performance, scalability, and numerical correctness.

Own end-to-end software integration across firmware, BSP, drivers, GPU software, services, and release systems. Lead system-level debugging of boot failures, crashes, resets, power transitions, performance regressions, and update issues. Analyze logs, traces, crash dumps, and hardware diagnostics to identify root causes, automate failure classification, integrate partner software, and coordinate cross-functional resolution across firmware, kernel, hardware, architecture, and OS teams.

Develop production tools, desktop applications, DCC integrations, and real-time workflow systems for Lightspeed Studios. Partner with artists and engineers to improve content pipelines, usability, reliability, performance, and automation. Build Python and Qt/PySide solutions, integrate applications such as Maya and Houdini with Unreal Engine, and explore agentic AI for content creation. The role requires extensive tools or pipeline engineering experience in games, VFX, animation, or real-time production.

Lead software architecture for DriveOS, decomposing requirements and integrating designs across system software, virtualization, graphics, compute, safety, security, sensor processing, and networking. Provide technical direction, resolve system-level issues, improve development processes, and communicate architecture decisions. Collaborate with software and hardware stakeholders to influence SoC and GPU designs for safe, reliable autonomous vehicle systems.

Develop compiler optimization algorithms for deep learning workloads, optimizing JAX and OpenXLA performance on NVIDIA GPUs. Design graph partitioning, tensor sharding, code generation, and performance-tuning solutions for distributed training and inference. Collaborate with deep learning framework and GPU hardware teams, implement user-facing JAX features, and contribute to production-grade software using MLIR, LLVM, and OpenAI Triton.