Assembly/Package Technology Development Quality and Reliability Intern
Job Description
Job Description
As a quality and reliability engineering intern, you'll join a team developing leading edge semiconductor package technologies for Intel's latest products. Assembly/Package reliability engineers take responsibility for setting reliability requirements to meet customer needs. We influence the design, material selection and process development of the new package technology to meet those needs. We use a wide variety of skills, from analytical models to advanced experimental designs to extensive data analysis, to evaluate and improve the package technology. Together with our technology development partners, we find the root cause of failure mechanisms and devise solutions.
Quality and reliability engineers are excellent data analyzers and analytical problem solvers in a high-paced, technically challenging environment. We measure our success by delivering world-class quality on cutting edge package technologies, faster and at a competitive cost.
This job might be for you, if:
- You like to find problems before they find you. You love taking on complex technical challenges and delivering robust solutions. You'll keep digging until you can explain the fundamental physics or chemistry behind the failure mechanism.
- You get a kick out of analyzing mounds of data and finding a pattern. You use data to drive decisions.
- You like working in a team to get results. You are persistent. You can keep others focused and aligned.
Cool Responsibilities:
- Innovate analytical and experimental methods to validate package technology reliability.
- Automate package interconnect technology design, process and material capability analysis using AI/ML methods and deliver "smart" decision making tools to accelerate innovation.
- Deliver analysis results and impact to multiple levels within the quality and reliability community and business partners.
The ideal candidate should exhibit the following behavioral traits:
- Problem-solving skills
- Analytical skills
- Working in a dynamic, results and team-oriented environment
- High tolerance for ambiguity
- Strong written and verbal communication skills
- Influence, strategic thinking, and leadership skills.
- Demonstrated strength in technical and analytical problem solving.
- Clarity in communication skills: able to make the complex simple and understood by a wide audience.
- Experience in predictive scientific data analysis algorithms with focus on Artificial Intelligence/Machine Learning
Qualifications
You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
Minimum Qualifications:
- Pursuing M.S. or Ph.D. in Materials Science, Mechanical Engineering, Physics or Chemistry. Electrical Engineering, Aerospace Engineering and Chemical Engineering candidates will also be considered, if they have relevant coursework or experience.
- 1+ years of Python experience.
Preferred Qualifications:
- Experience in data science and database management systems
- Experience in empirical data collection and statistical data analysis, reliability statistics, and design of experiments.
- Well organized, discipline and ability to manage tasks and time to ensure that business needs are met.