- Location
- China - Suzhou, Jiangsu - 122 Yong An Road
- Workplace
- Onsite
- Type
- Full-time
- Department
- Engineering
- Source
- Workday
Description
Work Schedule
Standard (Mon-Fri)Environmental Conditions
OfficeJob Description
Position Summary
The Test & Validation Engineer will support the development of Suzhou’s Validation & Reliability Center of Excellence by establishing validation methodologies, reliability testing capability, and product verification processes.
This role will be a key contributor to product transfer, NPI, quality improvement, and future product development programs.
Key Responsibilities
Product Validation
- Execute product performance validation testing.
- Conduct thermal mapping, temperature uniformity, and benchmark testing.
- Analyze product performance and generate technical reports.
Reliability Engineering
- Develop and execute reliability test plans.
- Support HALT, HASS, lifecycle, and stress testing.
- Recreate field failures and support root cause analysis.
Validation Governance
- Develop validation procedures and test methods.
- Define release criteria and validation gates.
- Maintain validation records and technical documentation.
NPI & Industrialization Support
- Support Alpha, Beta, Pilot, and launch activities.
- Validate design changes and engineering modifications.
- Participate in launch readiness reviews.
Laboratory Capability Development
- Support validation laboratory development.
- Improve instrumentation, automation, and data acquisition systems.
- Establish long-term validation expertise within Suzhou.
AI & Digital Engineering
- Utilize AI and analytics tools to accelerate validation data analysis.
- Build digital validation databases and knowledge management systems.
- Explore AI-assisted reliability prediction and failure pattern analysis.
Qualifications:
- Bachelor’s or Master’s degree in Mechanical Engineering, Refrigeration Engineering, Electrical Engineering, Physics, or related field.
- Experience in product testing, validation, reliability engineering, or laboratory environments.
- Familiarity with DOE, reliability methodologies, and data analysis techniques.
- Experience with data acquisition systems and instrumentation preferred.
- Knowledge of AI tools, data analytics, Power BI, Python, or equivalent digital platforms preferred.
Success Metrics:
- Support successful NPI and transfer project validation activities.
- Improve validation cycle time and test efficiency.
- Establish standardized validation methodologies and databases.
- Deliver at least one AI-enabled validation improvement project annually.
- Build foundational capability for future Validation & Reliability Center of Excellence