Top Tech Jobs & Startup Jobs in Seattle, WA

Provide advanced support and root-cause analysis for NVIDIA networking technologies in AI clusters. Reproduce and resolve customer issues, develop fixes and tools, analyze performance/tuning for high-performance lossless networks, collaborate with R&D and customers, and occasionally support outside regular hours.

Lead design and development of software to manage a fleet of GPU/DPU-accelerated Kubernetes clusters. Build automation, lifecycle management, CI/CD, and integrations to ensure performance, security, and reliability for large-scale AI infrastructure.

Lead product strategy and execution for NVIDIA's DSX OS AI infrastructure software: collaborate with customers and engineering, track AI infrastructure trends, support product marketing and documentation, enable developer ecosystems, solicit feedback from model and platform builders, and coordinate executive launches and demos.

Design and implement map-based driving algorithms and in-vehicle systems, integrate map and perception data, develop transformer-based graph models and LLM evaluation frameworks, build automated map content analysis and scalable distributed map-building workflows.

Provide advanced technical support for NVIDIA InfiniBand, NVLink and GPU-based HPC/AI infrastructure. Troubleshoot installations, networking and interoperability issues on multi-distro Linux, reproduce and resolve customer problems, use packet analysis and cluster tools, and collaborate with engineering, marketing, and support teams to improve processes and documentation.

Design and build a scalable failure-attribution framework for heterogeneous CPU/GPU clusters: collect high-fidelity telemetry, implement low-overhead tracing, automate root-cause classification (hardware, software, environment), and enable proactive resiliency measures like migration or checkpointing.

Lead technical pre-sales and solution integration for NVIDIA networking in AI/ML and HPC environments. Work with cloud providers, hyperscalers, and customers on POCs, performance debugging, workshops, and product strategy recommendations to drive adoption of NVIDIA networking hardware and fabrics.

Lead technical vision and strategy for next-generation graphics developer tools. Design and prototype tooling, drive cross-team initiatives, mentor engineers, engage external developers and partners, and deliver production-ready solutions that improve graphics development, debugging, profiling, and optimization workflows.

Design and implement CUDA/C++ libraries to accelerate Apache Spark DataFrame and I/O operations, collaborate on distributed multi-node GPU solutions, contribute to open-source projects (RAPIDS, CCCL, UCX), and drive testing, CI, and cross-platform optimization for enterprise deployments.

Partner with architecture and design teams to plan and execute functional and performance verification for GPU memory subsystem IP. Develop testbenches, BFMs, monitors and regressions, close coverage, enable FPGA/software testing, and support post-silicon verification and debug to sign off RTL.