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Data Engineering Student

Hajfa, Hajfa, Izrael Identyfikator oferty JR0270098 Kategoria Stażysta/Student Tryb pracy Hybrydowy Poziom doświadczenia Staż Wymiar etatu Praca na część etatu
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Job Description


The Yield Team is responsible for improving Intel's products yields.

We are seeking an exceptional data engineering student that will be responsible for developing Machine Learning automations as well as data transformation services and tools.

In this job you would have a chance to impact the next generation of Intel products while gaining experience in ML pipelines and working with big data.


Qualifications


  • Registered student for Information systems degree (specializing in Data)
  • At least 1.5 years till graduation - please specify in CV when you intend to finish the degree.
  • Available to work at least 20 hours a week (at least 2 days on site)
  • Highly motivated

Inside this Business Group


Manufacturing and Product Engineering (MPE) is responsible for test development across product segments, supporting 95% of Intel's revenue. We deliver comprehensive pre-production test suites and component/physical debug capabilities to enable high quality, high volume manufacturing.


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.

Benefits


We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing Benefits here.


Working Model


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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