Job description

QuantumScape is on a mission to transform energy storage with solid-state lithium-metal battery technology. The company’s next-generation batteries are designed to enable greater energy density, faster charging and enhanced safety to support the transition away from legacy energy sources toward a lower carbon future. About the team: Manufacturing Quality is a diverse group of engineers and data scientists who bring deep expertise in materials science, electrochemistry, statistics, and machine learning. Our team thrives on data-driven decision-making and a shared commitment to drive continuous improvement to QuantumScape’s solid-state battery technology. We work closely with the Manufacturing, Reliability, and R&D, groups to identify failure modes, refine critical-to-quality specifications, and implement robust control strategies across all process areas. What we need: We are seeking a Senior Engineer who has built their career on the manufacturing floor — as a process, manufacturing, yield, or quality engineer — and who uses production data to reduce variation. In this role, you will connect upstream process and metrology data to downstream yield, electrical test, and reliability outcomes, turn those correlations into specifications and control strategies, and drive them into production with process owners across QuantumScape’s cell and separator manufacturing lines. This is neither a data science role nor a quality-systems role: the ideal candidate pairs hands-on process knowledge with rigorous, practical data analysis, is passionate about optimizing tools and processes, and values consistency and documentation. If this role sounds like a good fit, we’d like to hear from you. What You’ll do: • Drive process variation down using production data: decompose variation by source (tool-to-tool, lot-to-lot, material and supplier, shift), quantify each contributor, and partner with process owners to eliminate the dominant ones, center and tighten process windows, and demonstrate sustained capability (Cpk) improvement. • Lead correlation projects that link upstream process parameters, material attributes, and in-line metrology to downstream yield, electrical test, and reliability outcomes; query and analyze the data with JMP or equivalent tools, and translate findings into concrete process, specification, and control changes on the manufacturing line. • Collaborate with process teams to identify yield improvement and defect reduction opportunities, confirm root cause through DOEs and engineering experiments, and lead improvement projects with process owners from problem definition to closure. • Develop subject-matter expertise on battery components and process steps; partner with process, equipment, and R&D engineers to define critical-to-quality (CTQ) characteristics and set specification limits grounded in process capability and product performance data. • Collaborate cross-functionally to establish repeatable measurement processes for cells and components, validated through MSA/Gage R&R, with results captured in the database and used as CTQs and specifications for process-quality tracking. Skills You’ll Need: • Bachelor’s degree in Engineering (Chemical, Mechanical, Materials Science, Electrical, Metallurgy, Industrial, or related discipline) + 5 years of experience in a process, manufacturing, yield, or quality engineering role; Master's degree + 3 years. • Hands-on experience as a process, manufacturing, yield, or quality engineer in a complex manufacturing environment (battery, semiconductor, display, data storage, or similar). • Demonstrated track record of reducing variation: isolating sources with variance components and multi-vari analysis, separating measurement from process variation, and sustaining Cpk gains. • Experience of driving correlation projects with production data and converting the results into specifications, control limits, or process changes that were implemented in production. • Strong applied statistics on manufacturing data in JMP or Minitab: regression, hypothesis testing, t-tests, ANOVA, DOE, SPC. • Working knowledge of quality tools — structured root cause analysis (Fishbone, 5 Whys, 8D), MSA (Gage R&R) • Excellent communication, presentation, and leadership skills — able to distill key insights from large data sets and influence stakeholders to drive quality and yield improvements. • Adaptable to shifting priorities in a fast-paced manufacturing environment and a first-principles thinker who reasons from underlying physics, process mechanics, and data rather than defaulting to convention. Nice to have: • Fundamental understanding of battery electrochemistries and failure mechanisms; familiarity with electrical test and metrics. • Six Sigma Green/Black Belt, Certified Quality Engineer (CQE), or equivalent. • Experience in cleanroom/dry-room manufacturing. • Programming skills, especially in Python Physical requirements: • Work is performed in a dry room, fume hood, lab area, or glovebox requiring the use of fine motor skills • Sitting or standing for extended periods of time • Reaching and twisting motions with hands • Lifting up to 25 lbs. ONSITE: This position is required to work onsite 5 days per week to meet the minimum essential duties and requirements of this position.  As an on-site R&D and manufacturing operations organization, in-person face to face interaction is essential to building authentic relationships, trust, teamwork, and collaboration.  Compensation & Benefits: Expected salary range for this role is from $112,500 to $163,200 and a final salary will be determined by the candidate's experience, educational background and internal equity. QuantumScape also offers an annual bonus and a generous RSU/Equity package as part of its compensation plan. In addition, we do offer a tremendous benefits plan including employee paid health care, Employee Stock Purchase Plan (ESPP), and other benefits.  We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive benefits and privileges of employment. Please contact us to request an accommodation.

Requirements

Must-haves

Hands-on experience as a process, manufacturing, yield, or quality engineer in a complex manufacturing environment (battery, semiconductor, display, data storage, or similar).
Demonstrated track record of reducing variation: isolating sources with variance components and multi-vari analysis, separating measurement from process variation, and sustaining Cpk gains.
Experience of driving correlation projects with production data and converting the results into specifications, control limits, or process changes that were implemented in production.
Strong applied statistics on manufacturing data in JMP or Minitab: regression, hypothesis testing, t-tests, ANOVA, DOE, SPC.
Working knowledge of quality tools — structured root cause analysis (Fishbone, 5 Whys, 8D), MSA (Gage R&R)
Excellent communication, presentation, and leadership skills — able to distill key insights from large data sets and influence stakeholders to drive quality and yield improvements.
Adaptable to shifting priorities in a fast-paced manufacturing environment and a first-principles thinker who reasons from underlying physics, process mechanics, and data rather than defaulting to convention.
Work is performed in a dry room, fume hood, lab area, or glovebox requiring the use of fine motor skills
Sitting or standing for extended periods of time
Reaching and twisting motions with hands
Lifting up to 25 lbs.

Nice-to-haves

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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningpython

Platform: successfactors
Effort: medium