Research Scientist, People and AI Research (PAIR)




Paris, France


Position summary

Google welcomes people with disabilities.

Minimum qualifications:

  • PhD in Computer Science, Artificial Intelligence, Machine Learning, a related technical field, or equivalent practical experience.

  • Experience writing machine learning code, prototyping with machine learning models and working with transformer models.

Preferred qualifications:

  • Experience working in an industry or academic research lab, and taking research from concept to products.

  • Experience using and advanced interpretability methods such as mechanistic interpretability, training data attribution or saliency.

  • Experience in research alignment and control of machine learning systems such as few short learning or parameter efficient methods.

  • Experience with symbolic computation and problem-complexity such as automated reasoning or complexity theory.

  • Contributions to publications related to machine learning problem complexity (https://e.g., NeurIPS, ICLR, ICML, CHI, EMNLP, ACL).

About the job

People and AI Research (PAIR) is a team in Google Research focused on Human-centered research and design to make AI partnerships productive. Our multidisciplinary team does fundamental research, invents new technology, and creates frameworks for design in order to drive a human-centered approach to AI.

In this role, you will be conducting research state-of-the-art on small problems, Machine Learning algorithms, interpretability, and visualization to better understand and control machine learning models, leverage small datasets, and improve applications of larger language-driven models. You will write Machine Learning code, coordinate with other teams, and develop, use, and contribute to emerging software systems and work with small and large language models. You will also work with others in PAIR and Google to explore new forms of interaction that can support the alignment of machine learning with human values.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.


  • Lead advanced research on small problems and interpretability to develop new algorithm insights for new alignable Machine Learning architectures.

  • Write Machine Learning code in frameworks like JAX, T5X, TFJS, etc.

  • Coordinate research efforts within PAIR and outside, manage objectives and priorities, and drive ambitious and thoughtful research directions towards alignable neural algorithms.

  • Present and disseminate research internally and externally, https://e.g. by contributing to interactive explorable visualizations (https://e.g., PAIR explorables), academic papers, and blog posts. 

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Why you should apply for a job to Google:

  • 56% say women are treated fairly and equally to men

  • 75% say the CEO supports gender diversity

  • Ratings are based on anonymous reviews by Fairygodboss members.
  • Generous parental and caregiver leave along with fertility and growing family support.

  • Flexible work options that include a hybrid work model, four “work from anywhere” weeks, and remote work opportunities.

  • A chance to be a part of a variety of employee resource groups, community groups, and culture clubs.