Job Details:Job Description: Advanced Packaging Technology and Manufacturing (APTM) Yield Group is looking for a Yield Analysis engineer to join our team tasked with the objective of driving yield and defect improvement across APTM portfolio of packaging technologies. As a yield analysis engineer, the successful candidate will set priorities for the team, get results across boundaries, ensure an inclusive work environment, and demonstrate progress to key yield milestones in technology development and high volume manufacturing phases. Our job is to understand where our manufacturing process, test content and inline metrologies need to be improved and fixed. We are looking for engineers who love solving technical problems, are driven to achieve results, and are flexible to adapt to new methods, tools, and fields of study depending on what is needed to solve the problem at hand. You will have access to extremely large datasets and the potential to become a technology expert.
Responsibilities will include:
Extract insights from structured and unstructured data by quickly synthesizing large volumes of data, applying statistical methods and machine learning techniques Develop solutions to problems by utilizing formal education, knowledge of manufacturing process, statistical knowledge, and problem-solving tools Independently drive recommendations and influence the Yield improvement roadmap .
Good understanding of the relationship between electrical and physical fails including a deep knowledge of FIFA, DFT, Sort/Test, Integration/Process Flow, Datamining, Databases, Data manipulation, and Data visualization.
Developing strong partnerships with diverse groups such as Process Engineering, Integration, QNR, and Product and Test Development Engineering.
Preparing detailed, clear, and timely reports summarizing the yield and device health. Owning determining the actions required to deliver Best in Class yield levels. Developing solutions to problems using process, Sort/Test and inline metrology knowledge, statistical knowledge, and problem-solving skills.
Work with both upstream, downstream and cross functional key partners to ensure successful technology development, transfer and ramp of new technology into HVM. Some domestic and international travel will be needed
The candidate should also exhibit the following behavioral traits or/and skills:
You must possess the below requirements to be initially considered for this position. Preferred qualifications are in addition to the requirements and are considered a plus factor in identifying top candidates
Minimum qualifications:
Bachelor's degree with at least 6 years of relevant experience, or Master's degree with at least 4 years of relevant experience, or PhD with at least 2 years of relevant experience in Materials Science and Engineering, Mechanical Engineering, Computer Science, Information Systems, Chemical Engineering, Electrical Engineering, Chemistry, Physics, or a related field.
3+ years of experience in data analysis through JMP, Python, or other data engineering software.
Preferred qualifications:
In-depth understanding and hands-on application of statistical analysis.
Demonstrated proficiency in structured technical problem-solving.
Demonstrated understanding of product design/circuit/architecture as relevant for yield analysis.
Demonstrated understanding of inline metrology capabilities as relevant for yield analysis.
Job Type:Experienced Hire
Shift:Shift 1 (United States of America)
Primary Location: US, New Mexico, Albuquerque
Additional Locations:
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: $164,470.00-232,190.00 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 be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.
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