Top Senior Hardware Engineer Jobs in Spokane, WA

Lead standardization strategy for optical transport and Ethernet technologies, develop and advocate contributions to standards bodies (ITU‑T, IEEE, OIF, OpenROADM), coordinate with PLMs and R&D, report progress internally, provide technical influence and guidance, and represent Nokia at standards meetings and industry events.

Pipeline hiring for hardware engineers at all experience levels. Work includes circuit board design, schematic capture, component selection and prototype bring-up, hardware debug/testing and failure analysis, integration with firmware/software teams, and design for manufacturability with production handoff.

Design and optimize high-speed, high-density ASIC package layouts and substrate breakouts. Perform pinout optimization, routing, placement, stack-up, power distribution, CAD library development, feasibility studies, and productivity methodology improvements while collaborating with package leads and cross-functional teams.

Design and perform physical layout for silicon interposers using Cadence Virtuoso; run DRC/LVS and verification (Calibre, ICV, Thunder); perform feasibility studies, floorplanning, custom layout, and collaborate with package, SI, and technology teams to meet schedule, cost, manufacturability, and electrical goals.

Design, build, and operate reliable backend systems while mentoring engineers, participating in design discussions, and improving system performance.

Design, test, and validate next-generation server hardware and components for performance, power, and reliability. Diagnose and resolve hardware issues across engineering and manufacturing, document results, and develop/maintain test scripts. Collaborate with internal teams and OEM/ODM partners to scale platforms for global deployment.

The Senior Package Layout Engineer will collaborate with teams to design IC substrates, optimize layouts, and improve productivity using Cadence tools.

The role involves optimizing hardware support within a software stack for AI model deployment, collaborating with teams and hardware vendors to enhance performance and portability across platforms.