Staff Engineer (Supplier Quality) (AI)

TL;DR

Staff Engineer (Supplier Quality) (AI): Managing end-to-end supplier qualification and quality audits with an accent on AI-driven quality analytics and predictive insights. Focus on automating quality tasks, building data-driven forecasting models, and optimizing supply chain risk management.

Location: Tokyo, Japan

Company

A global leader in data storage innovation, providing precision-engineered solutions to manage exponential data growth.

What you will do

• Manage end-to-end supplier qualification, periodic audits, and NPI readiness for scale.
• Develop supplier quality requirements, control plans (SPC), and process validation criteria.
• Lead root cause analysis and corrective actions using 8D and FMEA.
• Utilize AI/ML tools to identify defect trends, predict quality risks, and recommend corrective actions.
• Build and maintain performance dashboards using Power BI, Azure ML, or Tableau.
• Drive digital transformation and Six Sigma projects to reduce the cost of poor quality.

Requirements

• Bachelor's degree in Mechanical, Electrical, Industrial, Materials, or related engineering fields.
• 3–8 years of experience in supplier quality, manufacturing quality, or process engineering.
• Strong knowledge of quality tools including MSA, FMEA, 8D, and SPC.
• Experience working with manufacturers of disk drive or semiconductor related components.
• Must be based in Tokyo, Japan.
• Ability to travel frequently within or outside Japan at short notice.

Nice to have

• Experience using predictive analytics for defect reduction or supplier risk management.
• Background in AI-assisted inspection or computer vision.
• Six Sigma Green Belt or Black Belt certification.
• Knowledge of ISO9001 standards.

Culture & Benefits

• Join a global workforce of 29,000 employees driven by integrity, innovation, and inclusion.
• Opportunity to champion AI-enabled quality systems and drive digital transformation.
• Inclusive and equal opportunity employer environment.
• Focus on professional excellence in the datasphere.