Top Hardware Engineer Jobs in Richmond, VA

The Compliance Engineer ensures product certification processes for electrical and electronic equipment, oversees compliance activities, maintains relevant documentation, liaises with regulatory bodies, conducts risk assessments, and trains team members on compliance protocols.

Lead hardware design and development for NDR, collaborate with teams, define requirements, and innovate hardware products for enterprise-scale networks.

Design and implement SystemVerilog RTL for high-speed ASIC compute, memory, and networking subsystems. Define microarchitecture, optimize Power/Performance/Area, collaborate with verification/physical teams, prototype features with architects/software, mentor junior engineers, and improve design flow using AI and automation.

Lead manufacturing engineering efforts for assigned suppliers, manage delivery and cost-reduction projects, resolve technical issues, support sourcing and supplier selection, and drive supplier performance and process improvements across multiple part families.

Lead Manufacturing Engineer owns supplier technical performance, leads cross-functional problem solving and producibility improvements, supports supplier selection and source changes, influences cost and delivery, and frequently travels to suppliers.

The Senior Engineer will develop AI-driven hardware models, assess SystemC simulation efficiency, and integrate modeling with EDA tools.

The Senior Hardware Support Engineer will ensure production hardware reliability, coordinate vendor diagnostics, lead root cause analysis, and support engineering teams to enhance system stability.

The Lead Manufacturing Engineer coordinates multi-functional teams for hardware delivery, resolves technical issues with suppliers, and drives producibility improvements.

The Software Engineer will develop Python scripts for device testing and validation, ensuring production quality and reliability while automating factory processes.

As a System Engineer, you'll design, deploy, and maintain cloud systems for AI workloads, troubleshoot complex issues, and collaborate with teams to optimize performance.