Manufacturing Engineer: Lean NPI & DFx for Semiconductors

Applied Materials, Inc.; Austin (TX); On-site; USD 66,000 - 90,000; Full time

Job summary

Applied Materials, Inc. in Austin, TX is seeking a Manufacturing Engineer to develop and maintain manufacturing methods and processes for complex semiconductor equipment.

You will partner with Operations, Design Engineering, Quality, and NPI to ensure manufacturability, quality, and cost targets are achieved. You will lead ECOs, apply DFx methodologies, and analyze data to drive CAPA, cycle-time reductions, and continuous improvement.

Qualifications

• Bachelor's degree in Mechanical, Manufacturing, Industrial, Electrical, Chemical Engineering or related technical field.
• Experience in manufacturing environments with data-driven problem solving.
• Familiarity with Lean, Six Sigma, Kaizen and Continuous Improvement.
• Strong data analysis and communication skills.

Responsibilities

• Develop and maintain manufacturing methods, process flows, and work instructions.
• Support transfer of new products to manufacturing and ensure manufacturability and cost goals.
• Lead ECOs, PFMEA, control plans, and DFx methodologies to improve productivity and quality.
• Collaborate across Operations, Design Engineering, Quality, and NPI teams.
• Collect and analyze manufacturing data to drive CAPA and root cause analysis.
• Participate in problem-solving using 8D, 5-Why, Fishbone, and Pareto analyses.

Skills

Lean Manufacturing

Six Sigma

Problem solving

Communication skills

Cross-functional teamwork

Education

Bachelor's degree in Mechanical/Manufacturing/Industrial Engineering or related technical discipline

Tools

Excel

ERP/MRP (SAP/Oracle)

Job description

Applied Materials, Inc. in Austin, TX is seeking a Manufacturing Engineer to develop and maintain manufacturing methods and processes for complex semiconductor equipment.

You will partner with Operations, Design Engineering, Quality, and NPI to ensure manufacturability, quality, and cost targets are achieved. You will lead ECOs, apply DFx methodologies, and analyze data to drive CAPA, cycle-time reductions, and continuous improvement.