NPI Manufacturing Engineer - AI Compute Hardware

Job Title

NPI Manufacturing Engineer - AI Compute Hardware

Role Summary

Lead new product introduction (NPI) for MatX AI chips, compute trays, and rack-scale platforms into manufacturing. Collaborate with hardware, mechanical, quality, supply chain, test, and JDM/ODM partners to define and qualify manufacturing processes and drive production ramp.

Experience Level

Mid-level. Typical experience: 5+ years in NPI or manufacturing engineering for electronics, PCBs, servers, or AI compute hardware.

Responsibilities

Work across development and manufacturing to ensure products are ready for high-volume production.

• Manage NPI from EVT through DVT and PVT, owning manufacturing readiness, first-article builds, and process qualification with JDM/ODM partners.
• Develop and maintain manufacturing process flows, assembly procedures, work instructions, travelers, and production documentation.
• Lead SMT process development and optimization: stencil design, solder paste, reflow profiling, placement validation, solder quality, SPI, AOI, and X-ray inspection.
• Define and implement production tooling, fixtures, assembly equipment, and manufacturing test fixtures; develop production test processes (ICT, functional, boundary scan, system-level).
• Own yield improvement and defect reduction: defect tracking, Pareto analysis, root-cause, corrective actions, SPC, and process capability (Cpk) monitoring.
• Manage ECO and BOM change implementation with supply chain and manufacturing partners, including alternate component qualification and AVL updates.
• Support capacity planning and production ramp (line capacity, tooling, labor, process capability) and transition stable processes from NPI to mass production.
• Ensure compliance with ESD, packaging, handling, cleanliness, and material-control requirements for sensitive electronics.

Requirements

Must-have technical skills and experience. Nice-to-have items follow separately.

• 5+ years NPI or manufacturing engineering experience with PCB, server, AI compute, networking, or electronics hardware; proven experience through EVT/DVT/PVT and production ramp.
• Hands-on knowledge of electronics manufacturing and SMT processes: stencil design, solder paste, reflow, placement validation, SPI, AOI, and X-ray inspection.
• Experience developing and qualifying manufacturing processes for complex, high-layer-count PCB assemblies; strong DFM/DFA/DFT perspective.
• Experience developing manufacturing test processes, fixtures, and production test stations (ICT, functional, system-level).
• Proven skills in yield analysis and root-cause methodologies (defect tracking, 8D, FMEA, fishbone), SPC, and process capability analysis (Cpk).
• Hands-on experience working with JDM/ODM/CM partners for process reviews, first article builds, and qualification; familiarity with PLM/MES tools (Arena, Agile, or equivalent).
• Strong cross-functional collaboration across product engineering, hardware, mechanical, supply chain, quality, test, and manufacturing teams.

Nice-to-have / bonus:

• Experience with high-power AI accelerator or GPU server manufacturing and high-current PCB assemblies.
• Familiarity with liquid cooling assembly, leak testing, and coolant handling.
• Experience with rack-scale system manufacturing, OCP Open Rack, and system-level rack integration/testing.
• Familiarity with JTAG/boundary scan production testing and automated manufacturing test systems.
• Experience with high-volume production ramp and factory capacity planning.
• Knowledge of IPC-A-610, IPC-6012, IPC-7711/7721 or related manufacturing standards and experience implementing SPC and automated manufacturing data collection.

Education Requirements

Not specified.

About the Company

Company: MatX

Headquarters: Mountain View, California, USA

MatX specializes in creating faster chips for large language models (LLMs), focusing on innovative hardware and software solutions. The company fosters a collaborative and supportive work environment, welcoming candidates of all experience levels. Their approach prioritizes deep understanding and consideration of novel methods to drive efficiency and performance in their projects, particularly in silicon design and related engineering roles.