Daniel Galbraith




I’m a Linguist at Google. I enjoy working on cutting-edge NLP and all kinds of problems involving human language. I graduated from Stanford with a PhD in Linguistics (2018). I am excited about applying deep knowledge of how language works to useful projects in the tech industry.

I spent the last several years dedicated to human language research, developing a new approach to syntax. During PhD, I sourced, annotated and analysed large quantities of new linguistic data, using statistical and computational methods. You can see machine learning projects and research tools I built at my Github.


  • NLP / Computational Linguistics
  • Artificial Intelligence
  • Syntax & Phonology


  • PhD in Linguistics, 2018

    Stanford University

  • MPhil in Linguistics, 2013

    University of Cambridge

  • BA in Modern & Medieval Languages, 2012

    University of Cambridge





Jul 2021 – Present Mountain View, CA
Cross-functional work in Ads and Human Computation.

Research Scientist

Amazon Lab126

May 2020 – Jul 2021 Sunnyvale, CA
Research and development of NLP for Alexa for Halo (fitness band).

NLP Scientist


Nov 2018 – Apr 2020 Palo Alto, CA
Research and development of NLU engine for multi-language voice assistance.

Computational Linguist

Apple (via Welocalize)

Jul 2018 – Oct 2018 Cupertino, CA
Write daily patches & software updates for Siri speech recognition and text-to-speech.

Graduate Research Assistant & Teaching Assistant

Stanford University

Sep 2013 – Jul 2018 Stanford, CA
Linguistics research on syntax and metrical phonology with advisor Paul Kiparsky.


Better Linguistics for Better Voice Assistance

How we use linguistics to advance multilingual NLU.

What Faroese ballads and US presidential speeches have in common

Rhythm — or for linguists, a testing ground for phonological theory.

All Publications

(2018). The Predictable Case of Faroese. PhD thesis, Stanford University.


(2018). Sentence stress in presidential speeches. Prosody in Syntactic Encoding, Linguistische Arbeiten 573, ed. Gerrit Kentner and Joost Kremers.


(2016). A constraint-based account of Faroese ballad meter. NordMetrik: Versification, Metrics in Practice. University of Helsinki, 5/25/16-5/27/16.


(2013). Positional and Morphological Case in Faroese. Master’s thesis, University of Cambridge.


Data Scientist with Python

See certificate


  • 1600 Amphitheatre Pkwy, Mountain View, CA, 94043, United States