Lead Manufacturing Process & Yield Engineer

HP; Seberang Perai; On-site; MYR 90,000 - 140,000; Full time

Job summary

HP Malaysia is seeking a Manufacturing Process and Yield Engineer to contribute to engineering solutions across the product life cycle, optimize processes, and drive yield improvements.

You will lead cross-functional efforts, mentor staff, and collaborate with internal and outsourced partners to deliver robust, cost-effective manufacturing solutions.

Candidates should have a four-year engineering degree and 7–10 years of relevant experience, with knowledge of Lean, Six Sigma, and data analysis.

Qualifications

• Four-year Degree in Manufacturing Engineering, Mechanical Engineering, or related discipline.
• Typically 7-10 years of work experience in engineering design and solutions.

Responsibilities

• Leads the team in identifying problems and defects across manufacturing processes and outputs, and arriving at an appropriate resolution in yield related pareto.
• Provides guidance and mentoring to less-experienced staff to promote robust problem solving in yield-related projects.
• Designs portions of engineering solutions, including methods, operation sequences, and processes for manufacturing of parts and assemblies.
• Develops and distributes manufacturing documentation to support product design, configuration and build requirements.

Skills

Agile Methodology

Automation

Data Analysis

Lean Manufacturing

Manufacturing Engineering

Process Improvement

Project Management

Python

Software Development

Supply Chain

Systems Engineering

Tooling

Education

Four-year Degree in Manufacturing Engineering or Mechanical Engineering

Job description

HP Malaysia is seeking a Manufacturing Process and Yield Engineer to contribute to engineering solutions across the product life cycle, optimize processes, and drive yield improvements.

You will lead cross-functional efforts, mentor staff, and collaborate with internal and outsourced partners to deliver robust, cost-effective manufacturing solutions.

Candidates should have a four-year engineering degree and 7–10 years of relevant experience, with knowledge of Lean, Six Sigma, and data analysis.