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Intel

Process Integration, Yield, Defect Reduction Engineering Lead

Intel is hiring a Process Integration, Yield, Defect Reduction Engineering Lead. It pays $121k-$232k a year and Level rates it ; you can apply on Intel.

Level's read on this job

  • On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
  • Level classifies it as a lead role.
  • Level lists 863 other open roles at Intel.
  • The role was posted in the last few days.

AI in this role

Job Details:

Job Description:

The Role and Impact


As a Process Integration and Yield Engineer, you will play a pivotal role in driving technology improvement and manufacturing excellence. You will define process integration roadmaps, analyze large volumes of structured and unstructured data, and implement solutions that enhance quality, yield, and defect reduction. Working across internal and external teams, your contributions will directly support ramping advanced packaging solutions and sustaining high-volume manufacturing processes.

Business Group


Join Intel Corporation's global team responsible for advancing technology solutions that enable high-volume manufacturing and yield improvement. This group focuses on integrating innovative processes and driving continuous improvement, ensuring Intel delivers high-quality, reliable products for customers worldwide. Be part of a collaborative environment committed to shaping the future of technology and solving complex challenges.

Key Responsibilities


- Define and establish process flows, procedures, and equipment configurations for manufacturing modules.
- Extract insights from data using statistical analysis, coding, and machine learning techniques.
- Drive yield analysis and defect reduction initiatives to support process improvement.
- Conduct quality and reliability risk assessments for manufacturing materials and process changes.
- Collaborate with cross-functional teams to ensure successful technology transfer and ramp-up activities.
- Develop monitoring systems, dashboards, and methodologies to sustain and enhance manufacturing performance.
- Lead low yield analysis and yield improvement activities in both startup and high-volume manufacturing environments.


The ideal candidate should exhibit the following behavioral traits:


  • Strong troubleshooting skills and innovative problem-solving approaches.
  • Excellent verbal and written communication skills.

Qualifications:

Minimum Qualifications


- Bachelor's degree in Chemical Engineering, Electrical Engineering, Mechanical Engineering, Material Science, Microelectronics Engineering, Chemistry, Physics, or related field and 4+ year of experience.

OR

Master’s degree in the fields above with 3+ years of experience.

OR

PhD degree in the fields above with 1+ years of experience.

Experience listed above should be a combination of the following:

  • Experience in semiconductor manufacturing or advanced packaging.
  • Expertise in process integration, defect reduction, and backend interconnect or advanced packaging processes.
  • Experience in statistical analysis tools such as JMP, SQL, and statistical process control (SPC).
  • Experience with Design of Experiments (DOE) principles and Failure Mode Effects Analysis (FMEA)

Preferred Qualifications

  • Experience presenting yield summaries and engaging with external foundry customers.
  • Demonstrated ability to analyze defects and parametric data to drive yield improvements
  • Proven track record in new semiconductor technology development and transfer.


Take the next step to advance your career by joining Intel, where you can make a meaningful impact on cutting-edge technologies that shape the future.

Job Type:

Experienced Hire

Shift:

Shift 1 (United States of America)

Primary Location:

US, New Mexico, Albuquerque

Additional Locations:

US, Oregon, Hillsboro

Posting Statement:

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

Position of Trust

N/A

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $120,860.00-231,670.00 USD

The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.

Work Model for this Role

This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.

*

ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.

How we rate this

Process Integration, Yield, Defect Reduction Engineering Lead at Intel rates 27 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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