Top Tech Jobs & Startup Jobs in Seattle, WA

Build the developer ecosystem for NVIDIA Dynamo, an open-source distributed AI inference framework. Responsibilities include creating demos, sample code, documentation, videos, technical talks, workshops, and office hours; collaborating with inference projects and open-source maintainers; troubleshooting deployments; gathering developer feedback; influencing engineering and product priorities; and communicating progress externally. The role requires hands-on experience with model serving, Kubernetes, distributed inference, performance optimization, and developer or partner programs.

Provide advanced technical support for NVIDIA Ethernet switching and AI infrastructure products. Troubleshoot Linux, server, hardware, operating system, networking, installation, interoperability, and operational issues for enterprise customers. Analyze protocols and packet captures, lead critical issue resolution, collaborate with Engineering, Marketing, and Support, and develop support methodologies and documentation. The role focuses on data center, HPC, networking, and AI infrastructure environments.

Provides advanced software and customer support for NVIDIA networking technologies used in AI clusters. Reproduces and root-causes complex field issues to the source-code level, develops fixes and workarounds with R&D, analyzes high-performance network metrics, builds diagnostic tools, and supports technologies including InfiniBand, NVLink, and Spectrum-X. The role requires extensive C or Python experience in Linux or embedded systems, networking expertise, and strong customer communication.

Provides advanced technical support for NVIDIA networking and AI infrastructure products, including InfiniBand, NVLink, Ethernet, GPUs, Linux, and HPC environments. Troubleshoots customer issues across installation, operation, maintenance, interoperability, and performance. Responds through multiple support channels, collaborates with Engineering and Marketing, develops support methodologies, documents solutions, and improves internal support processes. Requires extensive networking, Linux administration, virtualization, containerization, cloud infrastructure, packet analysis, and customer debugging experience.

Provides advanced technical support for NVIDIA InfiniBand, NVLink, GPU, networking, and HPC infrastructure products. Responsibilities include troubleshooting customer issues across installation, operations, maintenance, interoperability, Linux environments, and performance; responding through multiple channels; collaborating with engineering and marketing; and documenting support methodologies. The role requires deep networking, Linux administration, virtualization, cloud, containerization, and HPC expertise, along with strong communication and customer problem-solving skills.

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.

Provide technical support to NVIDIA Enterprise customers by triaging and resolving issues, working with engineering on reproductions/logs, applying AI/ML and agentic AI to build support tools and products, documenting interactions and knowledge, and owning cases to resolution (occasional weekend/holiday support).

Support NVIDIA enterprise customers using GPU-accelerated platforms, triage hardware and AI/ML workload issues, collaborate with engineering teams, and drive cases through resolution. Develop support tools and products using AI, document customer interactions, and troubleshoot Linux-based multi-GPU systems, firmware, kernels, drivers, containers, and distributed workloads. The role also requires customer communication, technical analysis, and occasional weekend or holiday support.

Develop Rust-based, GPU-accelerated data processing frameworks and agentic retrieval pipelines for multimodal LLM applications. Build systems for dataset indexing, querying, deduplication, filtering, classification, benchmarking, and optimization. Collaborate with AI researchers and cross-functional teams to develop production tools, prototypes, and roadmaps. Apply prompt engineering, fine-tuning, profiling, and micro-optimization while supporting containerized cloud infrastructure, continuous delivery, peer reviews, and Gen-AI productivity products.

Leads the Kubernetes Runtime Engineering team responsible for tenant cluster configuration, container runtime reliability, GPU workload infrastructure, networking, storage, security, and multi-tenancy isolation. Manages engineers, drives architecture for fleet-scale cluster lifecycle operations, builds AICR lifecycle tooling, establishes hardening standards, partners across platform and cybersecurity teams, and represents runtime engineering in architecture, roadmap, customer, and open-source initiatives.