1 Quantumscape Manufacturing Specialist Jobs Hiring Near You

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: The Failure Analysis (FA) team plays a critical role in advancing next-generation battery technology by uncovering the true root causes behind defects and reliability issues. We are a highly collaborative, cross-functional group with deep expertise across engineering, chemistry, materials science, reliability, and manufacturing.
As an onsite R&D and manufacturing organization, we work closely with manufacturing, quality, metrology, and product engineering partners to rapidly learn from failures and translate insights into design and process improvements. The team increasingly relies on data analysis and machine learning to scale defect detection as production ramps. We value curiosity, rigor, teamwork, and hands-on problem-solving, and provide strong mentorship for early-career engineers.
What we need:We are seeking an Associate Failure Analysis Engineer (AMTS) who is intellectually curious, data-driven, and excited to build a foundation in failure analysis and reliability engineering. This is an early-career role ideal for a recent bachelor's or master's graduate who enjoys turning data into insight and solving problems systematically - no prior industry experience required.
You will work alongside experienced FA engineers to analyze failure-mode data, help characterize failure mechanisms in our solid-state battery cells, and translate findings into actionable feedback for the manufacturing and quality teams. Through structured mentorship and real project exposure, you will develop strong technical fundamentals, data and communication skills, and an understanding of how failure analysis informs design and manufacturing decisions at scale.
What you'll do:

• Analyze defect and reliability data across cell batches and test platforms to identify failure-mode patterns and trends
• Translate analysis into clear, actionable feedback and recommendations for the manufacturing and quality teams
• Apply statistical and data-analysis techniques (Python, JMP) to characterize failure modes and support process improvement
• Build and maintain dashboards, data summaries, and visualizations that help teams quickly understand key signals
• Support root-cause investigations alongside senior FA engineers, connecting data findings to physical failure mechanisms
• Draw on material characterization and electrochemistry fundamentals to interpret battery-related challenges
• Document findings in clear, well-structured technical reports and presentations
• Spend focused time in the lab as needed to observe characterization, review samples, and ground data analysis in the physical hardware

Skills you'll need:

• Bachelor's or Master's degree in Chemistry, Chemical Engineering, or Materials Science (or a closely related technical field); thesis not required; completed or expected by start date
• No prior industry experience required - this is an early-career / new-graduate role
• Strong data-analysis and problem-solving skills, with hands-on experience cleaning, analyzing, and visualizing data. Python preferred (e.g., pandas, NumPy, matplotlib); JMP is acceptable
• Familiarity with basic statistics, such as distributions, hypothesis testing, and regression
• Working knowledge of material characterization and electrochemistry fundamentals
• Ability to communicate technical findings clearly in writing and presentations, including to manufacturing and non-specialist audiences
• Comfortable working in and around a laboratory and manufacturing environment; hands-on lab experience is helpful

Nice to have:

• Statistical analysis experience beyond the basics (e.g., DOE, statistical process control / control charts, or reliability statistics)
• Machine learning coursework or projects, such as classification, defect detection, regression, or computer vision
• Experience building dashboards or data-visualization tools (e.g., Plotly/Dash, Streamlit, Tableau, or Power BI) and querying databases with SQL
• Familiarity with version control (Git) and reproducible analysis workflows (e.g., Jupyter notebooks)
• Internship, co-op, or research experience in an engineering, chemistry, or manufacturing environment
• Interest in energy storage, batteries, or high-reliability systems

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 4-5 days per week to meet the essential duties of the role. As an onsite R&D and manufacturing organization, in-person collaboration is important for building strong working relationships, accelerating learning, and solving complex technical challenges.
Compensation & Benefits:Expected salary range for this role is from $88,000 to $105,000, 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.