SMTS, Manufacturing Quality Engineer

QuantumScape Corporation•San Jose, CA

7d•$112,500 - $163,200•Onsite

About The Position

QuantumScape is seeking a Senior Engineer with hands-on manufacturing-floor experience as a process, manufacturing, yield, or quality engineer. The role uses production data to reduce variation by connecting upstream process and metrology data to downstream yield, electrical test, and reliability outcomes. The engineer will translate these relationships into specifications and control strategies and drive implementation with process owners across cell and separator manufacturing lines. This is a manufacturing engineering role, not a data science or quality-systems role, and requires practical data analysis, process knowledge, and consistent documentation. The Manufacturing Quality team includes engineers and data scientists with expertise in materials science, electrochemistry, statistics, and machine learning. The team works with Manufacturing, Reliability, and R&D to identify failure modes, refine critical-to-quality specifications, and implement process controls. The position is onsite five days per week and involves work in dry rooms, fume hoods, lab areas, or gloveboxes.

Requirements

Bachelor's degree in Engineering (Chemical, Mechanical, Materials Science, Electrical, Metallurgy, Industrial, or related discipline) and 5 years of experience in process, manufacturing, yield, or quality engineering; or a master's degree and 3 years of experience.
Hands-on experience as a process, manufacturing, yield, or quality engineer in a complex manufacturing environment such as battery, semiconductor, display, or data storage manufacturing.
Demonstrated ability to reduce variation by isolating sources using variance components and multi-vari analysis, separating measurement variation from process variation, and sustaining Cpk gains.
Experience leading production-data correlation projects and converting results into specifications, control limits, or process changes implemented in production.
Strong applied statistics skills for manufacturing data using JMP or Minitab, including regression, hypothesis testing, t-tests, ANOVA, DOE, and SPC.
Working knowledge of quality tools, including structured root cause analysis (Fishbone, 5 Whys, 8D) and MSA (Gage R&R).
Excellent communication, presentation, and leadership skills, including the ability to explain insights from large data sets and influence stakeholders to improve quality and yield.
Ability to adapt to shifting priorities in a fast-paced manufacturing environment and reason from underlying physics, process mechanics, and data.
Ability to work onsite five days per week.
Ability to perform fine motor tasks in a dry room, fume hood, lab area, or glovebox; sit or stand for extended periods; perform reaching and twisting motions with hands; and lift up to 25 pounds.

Nice To Haves

Fundamental understanding of battery electrochemistries and failure mechanisms, and familiarity with electrical testing and metrics.
Six Sigma Green Belt or Black Belt, Certified Quality Engineer (CQE), or equivalent.
Experience in cleanroom or dry-room manufacturing.
Programming skills, especially in Python.

Responsibilities

Use production data to decompose process variation by source, quantify contributors, and work with process owners to eliminate dominant sources, center and tighten process windows, and demonstrate sustained Cpk improvement.
Lead projects correlating upstream process parameters, material attributes, and in-line metrology with downstream yield, electrical test, and reliability outcomes; analyze data using JMP or equivalent tools and translate findings into production process, specification, and control changes.
Partner with process teams to identify yield improvement and defect reduction opportunities, confirm root causes through DOEs and engineering experiments, and lead improvement projects from problem definition through closure.
Develop subject-matter expertise in battery components and process steps, and partner with process, equipment, and R&D engineers to define CTQ characteristics and specification limits based on process capability and product performance data.
Work cross-functionally to establish repeatable measurement processes for cells and components, validate them through MSA/Gage R&R, and capture results in the database for use as CTQs and specifications in process-quality tracking.