NVIDIA

Semi-conductor

Manager,ProductQualityEngineering

Taiwan FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Director candidates.

The Brief

“Manager, Product Quality Engineering at NVIDIA. Skills: Product Quality Engineering, Failure Analysis, Team Leadership. Manage Product Quality Engineering team. Focus on failure analysis”

What You'll Achieve.

Drive for product quality improvements; Product quality improvement initiatives; Product quality improvement programs

Industry & Context.

Semi conductor
Problems you'll solve

Problem-solving skills

What They're Looking For.

Must Have

Bachelor or master’s degree in electronic engineering or related fields, 10+ overall years of experience in Semi-conductor or Datacenter industry, 8+ years of experience at management level, Failure analysis expert in electronic products with knowledge of failure analysis tools, techniques, and methodologies, Data analysis expert who understands chip parametric and reliability requirements, Excellent quality mindset and problem-solving skills, leadership skills and people skills, Verbal and written communication skills in English and Mandarin

Nice to Have

Good knowledge of product infrastructure and test methodology, Great background of Hoshin/SWOT process, technical/debug skills in Data Center products

What You'll Do.

Manage Product Quality Engineering team

Focus on failure analysis

Provide guidance and coaching

Coordinate with engineering teams

Root cause customer quality issues

Determine corrective actions

Ensure effectiveness of actions

Define quality standards

Implement quality standards

Monitor product quality performance

Report Quality Metrics

Collaborate with engineering team

Develop failure analysis tools

Develop failure analysis methodology

Support continuous improvement

Fulfill internal quality requirements

Fulfill internal audits

How You'll Work.

Team & Collaboration

Work closely with various engineering teams; Coordinate with internal and external engineering team; Collaborate with engineering team

Communication Scope

Excellent communication skills; Verbal communication skills; Written communication skills

Process & Methodology

Product quality improvement initiatives, Product quality improvement programs

Full Job Description

We are looking for a Product Quality Engineering Manager in Taiwan Product Quality Engineering Lab. This is a role focusing more on engineering aspects. You will be responsible for leading and mentoring a team of product quality engineers focusing on in-depth chip, board and system failure analysis on customer quality complaints. You will also be tracking quality metrics. Moreover, you will work closely with various engineering teams to drive for product quality improvements. Your strong management experience, technical background, quality mindset and excellent communication skills are essential as you will be leading NVIDIA product quality improvement initiatives and programs. **What you’ll be doing:** * Manage the Product Quality Engineering team focusing on failure analysis. * Provide guidance, feedback and coaching to the staffs on quality process and best practices. * Coordinate with internal and external engineering team to root cause customer quality issues. * Determine the corrective and preventative actions and ensure the effectiveness of these actions. * Define and implement quality standards, metrics, processes, and tools for NVIDIA products. * Monitor product quality performance and report Quality Metrics. * Collaborate with engineering team to develop new failure analysis tools and methodology. * Support continuous improvement activities and fulfill internal quality requirements and audits. **What we need to see:** * Bachelor or master’s degree in electronic engineering or related fields. * 10+ overall years of experience in Semi-conductor or Datacenter industry. * 8+ years of experience at management level. * Failure analysis expert in electronic products with strong knowledge of failure analysis tools, techniques, and methodologies. * Data analysis expert who understands chip parametric and reliability requirements. * Excellent quality mindset and problem-solving skills. * Strong leadership skills and people skills. * Verbal and written communication

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