Top Tech Jobs & Startup Jobs in Seattle, WA

Lead HBM and LPDDR system integration and bringup for next-generation SoCs. Own memory performance, power, thermal, and reliability closure across silicon, package, board, and firmware. Drive post-silicon margining, VF shmoo, eye characterization, and correlation. Debug training, calibration, SI/PI, and system stability issues. Define validation, characterization, and issue-tracking plans to produce production-ready operating points.

The role involves validating clocking structures in products, developing test plans, automation, and partnering with design teams to ensure high-quality verification of ASIC designs.

Develop end-to-end perception solutions for autonomous driving, leveraging deep learning and data-driven approaches to enhance system accuracy and efficiency.

Design and optimize high-performance C++/CUDA libraries for GPU-based data processing. Improve multi-node GPU communication (UcxExchange), optimize Presto GPU query performance, and lead enhancements across Presto, Velox, and cuDF projects for efficient DataFrame and database acceleration.

The Senior Formal Verification Engineer will verify ASICs using formal verification methods, ensuring correctness and collaborating with architects and designers across projects.

Design, build, and optimize GPU‑accelerated inference software and open‑source frameworks (vLLM, SGLang, FlashInfer). Improve performance and scale for LLMs and generative models across NVIDIA GPUs and edge SoCs using CUDA, CUTLASS, Triton, NCCL and profiling tools. Collaborate across teams to enable efficient model serving and deployment.

The Senior Formal Verification Engineer will verify sophisticated ASIC builds using formal methods, collaborate with architecture teams, develop verification environments, and support silicon debug.

Own design, automation, and lifecycle of Kubernetes platform for global network infrastructure. Build production-quality tooling for cluster provisioning, upgrades, GitOps delivery, observability, and recovery. Provide production support and incident response for network services on the platform, drive root-cause analysis, and establish platform standards and runbooks.

Advise ISVs on designing, deploying, and optimizing large-scale accelerated AI infrastructure. Lead architecture reviews, POCs, benchmarks, and production deployment guidance across compute, networking, storage, containers, orchestration, observability, and CI/CD. Create reference architectures, sizing guidance, technical playbooks, demos, and whitepapers. Support cluster monitoring, reliability, and performance improvements. Up to 20% travel for customer engagements.

Serve as a customer-facing solutions architect for CAE/CFD/FEA ISVs and OEMs, accelerating simulation and digital-twin workflows on NVIDIA platforms. Advise on GPU-acceleration, physics-informed ML/surrogate modeling, Omniverse integration, architecture analysis, and deliver trainings, demos, and prototypes to improve performance and simulation cycles.