Manufacturing Engineering Intern – PCB at d-Matrix in Santa Clara, CA

Summary: d-Matrix is focused on unleashing the potential of generative AI to power the transformation of technology. They are seeking a motivated Manufacturing Engineering Intern to join their Operations team, focusing on overseeing the PCB life cycle from initial layout through fabrication. Responsibilities: - Design-to-Release Orchestration: Participate in the full PCB design release process, including reviewing Gerber files, validating stack-ups, and resolving DFM (Design for Manufacturing) queries from external fabrication vendors - Supplier Yield Monitoring: Track and analyze manufacturing yields at PCB suppliers; provide regular performance readouts to the Operations team and identify specific process areas for improvement - Quality & Compliance: Support bare PCB qualification and acceptance testing in strict accordance with IPC standards (IPC-A-600/610) - Cross-Functional Analysis: Perform detailed data analysis on test coupon measurements, collaborating directly with Signal Integrity (SI) leads to ensure physical boards meet high-speed performance requirements - Technology Research: Conduct market research on emerging PCB technologies, advanced substrate materials, and new supplier capabilities to build a strategic internal knowledge base Required Qualifications: - Currently pursuing or recently completed a B.S. or M.S. in Electrical Engineering - Understanding of PCB stack-up architecture, trace routing constraints - Familiarity with (or a strong desire to learn) IPC standards for board acceptability and fabrication tolerances - Exposure to ECAD tools such as Altium Designer or Cadence - Basic proficiency in SQL or data visualization tools for analyzing yield and performance - Excellent problem-solving skills with a focus on hardware reliability, failure analysis, and data-driven decision-making Required Skills: PCB fundamentals, PCB stack-up architecture, Trace routing constraints, IPC standards, ECAD tools, Altium Designer, Cadence, SQL, Data visualization, Hardware reliability, Failure analysis, Data-driven decision-making