Top Tech Jobs & Startup Jobs in Seattle, WA

Leads site reliability operations and Tier 3 enterprise support across identity, messaging, compute, endpoints, databases, networking, and datacenter infrastructure. Owns incidents, SLAs, compliance, vulnerability remediation, asset management, root-cause analysis, automation, and permanent fixes. Provides technical leadership and mentoring, supports executives, coordinates with global platform teams and vendors, leads site projects and major incidents, and represents local priorities in regional and global IT initiatives.

Design and optimize agentic AI systems for NVIDIA’s CUDA ecosystem, including agent architectures, multi-agent workflows, tool use, memory, orchestration, training, verification, reward, and evaluation systems. Co-design AI systems across models, inference, compilers, runtimes, libraries, kernels, and GPUs. The role requires strong C/C++, Rust, and Python skills, GPU programming expertise, and experience with agent systems, reinforcement learning, or modern AI inference.

Supports and root-causes complex customer issues involving NVIDIA networking and AI cluster technologies. Develops bug fixes, workarounds, diagnostic tools, and performance-tuning recommendations in collaboration with R&D and support teams. Works with InfiniBand, NVLink, Spectrum-X, and high-performance lossless networks, analyzing logs, traces, metrics, and source code. Provides customer support and may work occasional weekends or holidays.

Develop and debug cloud-native solutions for AI/ML datacenters, focusing on Kubernetes and Slurm enhancements and customer workflows.

Develop and guide sensor fusion functionality for autonomous driving by creating 3D world models and ensuring accurate representations using various signals. Lead technology approaches and mentor team members while adhering to automotive quality standards.

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.

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.

Define system and technical requirements for fault-tolerant quantum computing across hardware, software, and firmware. Develop real-time quantum error correction and calibration approaches, perform systems analysis across qubit modalities, and create and review test cases. Collaborate with product, research, engineering, and external partner teams to advance quantum control systems, quantum computing products, and related NVIDIA technologies.

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.

Develop and implement core firmware features for Mellanox NICs supporting cloud, HPC, and storage networking. Collaborate with architecture and software teams, create verification tests, debug complex hardware/software systems, and contribute to firmware maintenance, qualification, and releases. The role requires strong C/C++ development, networking knowledge, PCIe and virtualization experience, scripting skills, and familiarity with distributed, high-performance computing environments.