FEOL Dry/Plasma Process Engineer for Impact & Improvement

Texas Instruments; Dallas (TX); On-site; USD 85,000 - 120,000; Full time

Job summary

Texas Instruments is seeking an energetic Manufacturing Process Engineer to support 24/8 operating shifts and drive continual improvement across manufacturing procedures and processes. You will be responsible for improving efficiencies, yields, machine operations, and quality in a high-volume 300mm wafer fabrication environment, identifying and solving systematic problems, and supporting ramp activities.

The role emphasizes data-driven analysis, process experiments, and cross-functional

Qualifications

• B.S. in an engineering discipline; knowledge of manufacturing processes.
• Strong analytical and problem-solving abilities; data-driven decision making.
• Experience with process improvement and yield optimization.

Responsibilities

• Support 24/8 manufacturing operations.
• Develop and implement improved methods of manufacturing, procedures, and processes that improve efficiencies, yields, machine operations, and quality.
• Implement project or improvement plans for efficiency, cost reduction, quality, or new product support.
• Perform lot and equipment dispositions to support continuous production flow and minimize cycle time in high-volume manufacturing.
• Identify systematic problems in process or equipment and communicate findings to engineering staff.
• Support ramp with startup of equipment/process and run SWRs (process experiments).
• Participate in data analysis and problem resolution.

Skills

Process engineering

Manufacturing

Data analysis

Problem solving

Continuous improvement

Education

Bachelor's degree in engineering

Job description

Texas Instruments is seeking an energetic Manufacturing Process Engineer to support 24/8 operating shifts and drive continual improvement across manufacturing procedures and processes. You will be responsible for improving efficiencies, yields, machine operations, and quality in a high-volume 300mm wafer fabrication environment, identifying and solving systematic problems, and supporting ramp activities.

The role emphasizes data-driven analysis, process experiments, and cross-functional