Deadline extension: AI Residency Program at X, the moonshot factory

Venn diagram of Google X research
January 22, 2019

The X AI Residency application deadline has been extended from January 15, 2019 to February 11, 2019.

X AI Residency


At Alphabet (formerly Google) X, we create breakthrough technologies to help solve some of the world’s hardest problems. AI is ushering in a new generation of moonshots and moonshot-takers at X. Our residency program is geared towards those who want to apply their AI abilities in experimental yet highly practical ways to make meaningful progress against seemingly intractable problems.

Duration: 12 weeks
Location: X’s headquarters in Mountain View, California
Expected Start Date: from ~May 27th, 2019  (can accommodate different start dates)
Application Deadline:  February 11, 2019
Program website:
Requirements: Candidates must be enrolled in an academic program and be working toward completing their Masters or  PhD degrees.

During this X AI Residency individuals can expect:

  • Competitive pay
  • Full relocation and housing costs subsidized related to the residency program
  • To be part of a lively community of other X AI Residents for a weekly colloquium, tech talks from AI leaders from across X and external organizations, among other activities.

Responsibilities may include:

  • Collaborating with a secretive or public X Project or team on applying AI to their mission
  • Understanding the project’s challenges
  • Suggesting a number of ways in which AI can apply to those challenges
  • Prototyping solutions through applying AI
  • Working closely with cross functional Xers to develop working solutions
  • Implementing algorithms
  • Engaging with the X residency community during the 12 week program

Minimum Qualifications:

  • Currently enrolled in a Masters or Phd program in a STEM field such as CS, Physics, Chemistry, Neuroscience or Mathematics/Statistics with a strong interest in machine learning.
  • Completed coursework in calculus, linear algebra, and probability, or their equivalent.
  • Experience with one or more general purpose programming languages, including but not limited to: Python, Java, C/C++
  • Experience with machine learning systems, algorithms or applications such as: deep learning, computer vision, robotics, optimization, on-device learning, nlp, audio/speech recognition, signal processing or time-series analysis.

Preferred Qualifications:

  • Experience working with TensorFlow
  • Open-source projects that demonstrate relevant skills  and/or publications in relevant conferences and journals (e.g. NIPS, ICML, ICLR, CVPR, ICCV, ECCV, ICASSP)