Top Tech Jobs & Startup Jobs in Seattle, WA

Design and develop real-time online mapping algorithms for autonomous vehicles, generating 3D world models and enriched BEV representations from sensor and external data. Build efficient, safety-compliant embedded C++ software and CUDA-accelerated solutions for NVIDIA’s autonomous driving platform. Responsibilities include sensor fusion, computer vision, state estimation, algorithm integration, runtime optimization, and collaboration across engineering teams.

Design and optimize multi-agent AI systems for NVIDIA’s CUDA ecosystem, including agent runtimes, compiler-integrated orchestration, evaluation frameworks, and GPU-centric performance solutions. Collaborate across hardware, software, algorithms, compilers, kernels, frameworks, distributed training, and inference teams to accelerate agent planning, tool use, code generation, and other AI workloads.

Lead technical program management for NVIDIA GPU software, including kernel components, drivers, and firmware. Align chipset and product roadmaps with software capacity, coordinate cross-functional dependencies, make prioritization decisions, partner with hardware and customers, improve planning systems, and track execution metrics. The role requires extensive software product delivery experience and supports process improvements across graphics, machine learning, and accelerated computing programs.

Lead the definition, delivery, enablement, and market adoption of NVIDIA accelerated compute platforms. Manage hardware SKUs, platform specifications, schedules, system concepts, partner requirements, certifications, RMA policies, and ecosystem collateral. Represent enterprise, HPC, and cloud customer needs while coordinating with hardware vendors, OEMs, software and firmware partners, and internal teams. Drive go-to-market messaging, technical documentation, design-win processes, and system-level trade-off analysis involving costs, reliability, performance, and platform roadmaps.

Develop and optimize NVIDIA’s proprietary C++ GPU compiler backend. Responsibilities include designing compiler passes, improving code generation and machine instruction performance, supporting GPU architectures, and collaborating with compiler, hardware, and application teams. The role requires strong C++ and compiler code-generation expertise, with preferred experience in LLVM, instruction scheduling, register allocation, CUDA, DirectX, OpenGL, and Vulkan.

Lead the design and optimization of GPU-cluster infrastructure supporting AI and ML research. Partner with researchers, data engineers, and DevOps teams to identify bottlenecks, improve researcher efficiency, and build scalable, highly available systems. Drive infrastructure roadmaps, optimize resource utilization, define performance metrics, and oversee distributed training operations across HPC environments. The role requires deep expertise in accelerated computing, storage, scheduling, networking, containers, cloud platforms, and AI/ML frameworks.

Build and operate NVIDIA’s serverless AI inference platform across globally distributed, GPU-backed Kubernetes clusters. Lead feature implementation, testing, performance optimization, reliability improvements, customer issue resolution, reference architecture development, and technology evaluation. Mentor engineering teams on scalable AI/ML workloads and contribute to product requirements and roadmap development.

Design, develop, test, and optimize system software for NVIDIA ARM-based SoCs across pre-silicon and post-silicon phases. Analyze bottlenecks, optimize performance, develop benchmarking tools, evaluate CPU and GPU workloads, and conduct competitive architecture and performance analysis. The role requires collaboration and communication with internal and external audiences.

Develop autonomous driving systems that fuse mapping and perception data into real-time 3D world models. Build BEV models, occupancy grids, obstacle representations, and occlusion masks to support mapless navigation and scenario understanding. Collaborate with perception and planning teams, write reliable production-quality code, and apply automotive safety practices. The role also involves advanced computer vision, geometry, sensor calibration, and state estimation algorithms for autonomous vehicles.

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.