Quality & Reliability Engineering Intern

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Meta

10,001+ employeesMenlo Park, CASoftware Development
Actively hiringPaidSoftware Development
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Best applied by Nov 19

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About the role#

Reality Labs builds hardware for virtual, augmented, and mixed reality experiences. We are looking for a Quality and Reliability Engineering intern to join our team. You will focus on hardware issues through test development, failure analysis, and data synthesis. This is a 12-week internship.

What you'll do#

  • Create reliability tests and conduct specification research.
  • Design quality control procedures and sampling plans.
  • Collect quality and reliability data from various sources to build insights.
  • Build dashboards that update based on incoming data.
  • Share your findings with the leadership team.

What you'll need#

  • Currently pursuing a Bachelor's, Master's, or PhD in engineering or science, including fields like mechanical, electrical, industrial, or chemical engineering, physics, chemistry, or materials science.
  • Basic knowledge of engineering principles.
  • Experience with data science and programming tools such as Tableau, JMP, SQL, Python, R, or Google Suite.
  • Ability to work both independently and with a team.
  • Intent to return to your degree program after the internship.
  • Must have valid work authorization at the time of hire and throughout the internship.
  • Familiarity with quality or reliability engineering principles is helpful.
  • Experience with Monte Carlo simulations, forecasting techniques, or advanced machine learning and AI tools is a plus.

Location & details#

  • Location: Sunnyvale, California.
  • Modality: On-site.
  • Duration: 12 weeks.
  • Compensation: $6,688 to $11,880 per month.

About Meta

Meta develops software and social media applications. It operates platforms such as Facebook, Messenger, Instagram, and WhatsApp. The company maintains headquarters in Menlo Park, California. Current work focuses on augmented and virtual reality alongside artificial intelligence and machine learning.

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