Quality & Reliability Engineering Intern

Meta•Sunnyvale, CA
•$6,688 - $11,880

About The Position

At Reality Labs, the team explores, innovates, and designs hardware for next-generation virtual, augmented, and mixed reality experiences. The Quality & Reliability Engineering Intern will contribute to quality control procedure development, reliability test development and specification research, and failure analysis for hardware issues. The role involves consolidating information from multiple sources to develop insight-rich dashboards. The internship lasts 12 weeks.

Requirements

  • Currently possess or be pursuing a bachelor's degree in engineering or science, such as reliability engineering, materials science, mechanical engineering, chemical engineering, electrical engineering, industrial engineering, physics, or a related field.
  • Basic fundamentals in engineering principles.
  • Basic fundamentals in data science skills and basic programming, particularly Tableau, JMP, SQL, Python/R, and Google Suite.
  • Ability to work independently and as part of a team.
  • Must obtain work authorization in the country of employment by the time of hire and maintain ongoing work authorization during employment.
  • Intent to return to a degree program after completing the internship/co-op.

Nice To Haves

  • Currently possess or be pursuing a master's or PhD degree in engineering or science, such as reliability engineering, materials science, mechanical engineering, chemical engineering, electrical engineering, industrial engineering, chemistry, physics, or a related field.
  • Familiarity with quality or reliability engineering principles.
  • Experience with Monte Carlo simulations, modelling tools, and forecasting techniques.
  • Experience with advanced data science, database, or ML/AI tools.

Responsibilities

  • Drive reliability test development and specification research.
  • Formulate quality control procedures and sampling plans.
  • Source quality and reliability data from disparate sources to create insights.
  • Develop dynamic and durable dashboards derived from evolving datasets.
  • Present insights to the leadership team.
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