Top Tech Jobs & Startup Jobs in Seattle, WA

Leads NVIDIA’s AI Cluster Runtime product, setting direction for a validated, reproducible GPU Kubernetes software stack. Expands support across accelerators, clouds, and AI workloads; oversees version-locked recipes, supply-chain provenance, and reliable deployment. Represents the project to customers, partners, and the open-source community while driving community adoption. Requires deep Kubernetes GPU infrastructure expertise, GitOps configuration delivery experience, and a strong open-source contribution record.

Lead and grow a technical team responsible for verifying AI compilers for next-generation workloads. Define formal verification requirements, drive AI-assisted and compiler-aware verification (fuzzing, differential testing, symbolic reasoning, formal methods), and partner with compiler, CUDA, runtime, and ML framework teams to build scalable verification infrastructure and improve production confidence.

Design and develop RTOS and hypervisor features, bring up and optimize software stacks on NVIDIA Tegra SoCs, and debug system-level issues across hardware, firmware, RTOS, and virtualization layers. The role develops high-integrity automotive software using safety and security practices, while leading cross-team technical initiatives and coordinating execution. Candidates need strong C/C++ systems programming, embedded software expertise, operating-system knowledge, hardware-assisted virtualization experience, and at least eight years of experience.

Lead performance characterization and optimization of large-scale AI workloads across GPUs, networking, storage, and software. Design and run benchmarks and profiling, diagnose bottlenecks, define evaluation methodologies and metrics, produce actionable optimization plans, and collaborate with DL engineers, platform teams, and GPU architects to deliver improvements.

Lead development of local AI agent frameworks and runtimes on Windows and GeForce RTX GPUs. Optimize agent inference, sandboxing, and privacy/security policies, collaborate with AI research and driver teams, mentor engineers, and deliver production-ready, local autonomous agent systems.

Develop silicon-accurate GPU kernel microbenchmarks, model-level performance analysis, and agentic kernel optimization to maximize LLM inference throughput and latency. Attribute bottlenecks across kernel, compiler, and runtime, produce optimization policies, and collaborate with compiler, hardware, kernel, and framework teams to deliver production-grade performance improvements.

Develop and optimize Vulkan graphics drivers to maximize performance, power-efficiency, and latency for games and creative apps. Diagnose GPU/CPU bottlenecks, implement driver performance improvements, fix defects, collaborate across teams, and communicate API usage changes to third-party developers.

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.

Develop and deploy scalable AI solutions, distributed training and inference systems, and MLOps pipelines across cloud and NVIDIA platforms. Serve as a technical lead for customers and partners, optimize large-scale workloads for performance and cost, diagnose full-stack infrastructure problems, and create open-source tools and reference architectures. The role requires strong AI/ML lifecycle experience, systems expertise, programming skills, and communication abilities.

Lead product strategy and multi-quarter roadmaps for NVIDIA’s AI Factory software-defined networking stack. Guide upstream development across OVN, OVS, and OVN-Kubernetes; define requirements, priorities, and architecture trade-offs; coordinate dependencies across DPU, fabric, virtualization, and engineering teams; and translate partner and operator needs into product releases, reference deployments, and community strategy.