Hardware Analytics, Intern

(Menlo Park, CA)

Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities — we're just getting started.

Facebook is seeking a Hardware Analytics, Intern to join our Release to Production Engineering team. Come learn about our cutting edge power and hardware architecture, which has one of the most efficient infrastructures in the industry. Our servers and datacenters are the foundation upon which our rapidly scaling infrastructure efficiently operates and upon which our innovative services are delivered.


  • Interface with internal hardware, software engineers and operations teams to understand system architectures and failure modes
  • Proactively create experiments and data visualizations to detect and diagnose hardware health issues, focusing on systemic solutions
  • Develop data pipelines and discover insights to answer relationship between hardware and data center parameters to server failures
  • Troubleshoot, diagnose and root cause of system failures and isolate the components /failure scenarios while working with stakeholders internally and externally
  • Share insights with stakeholders and software teams to develop architectures to handle server failures based on hardware health data

Minimum Qualifications

  • Pursuing a degree in engineering, statistics, math, or related field
  • Programming experience
  • Scripting experience
  • Knowledge of Linux
  • Troubleshooting and data tooling skills (data analysis, big data, building analytical models, visualizations)
  • Communication Skills
  • Ability to obtain and maintain work authorization in the United States in 2018

Preferred Qualifications

  • Pursuing a doctoral degree in engineering, statistics, math, or related field
  • Past experience or coursework related to computer & systems architecture, statistics, machine learning, networking etc.

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