Ux Researcher, Core, Data Ux, AI Foundations

Google Google · Big Tech · San Jose, CA +3

This role is for a UX Researcher within Google's Core AI Foundations organization. The primary focus is on understanding and optimizing the workflows of ML researchers, data engineers, and AI/ML developers by conducting primary research, including field studies, interviews, and usability testing. The goal is to inform the design of next-generation AI-driven tools and agentic systems, ensuring products are useful, usable, and helpful.

What you'd actually do

  1. Conduct research to identify bottlenecks and drive improvements in the efficiency of Googlers building, training, and deploying AI models, systems, and agents.
  2. Contribute research insights that inform the design of next-generation, AI-driven UIs and workflows, moving beyond traditional interfaces.
  3. Execute evaluative research (e.g., usability studies, heuristic evaluations) on internal tools that support AI development cycles, data governance, and agentic systems within the data UX portfolio.
  4. Use and experiment with internal AI/ML-powered tools for analyzing and synthesizing complex research data (both qualitative and quantitative to generate novel insights and efficiencies).
  5. Collaborate with product managers, engineers, and UX designers to define research questions.

Skills

Required

  • research design utilizing various methods including, usability studies, contextual inquiry, and surveys
  • research methods (e.g., usability, studies, contextual inquires, 1:1 interviews, unmoderated research studies)
  • Artificial Intelligence (AI) or Machine Learning (ML)

Nice to have

  • Master's degree or PhD in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, or related field
  • conducting UX research on products and working in a large, matrixed organization
  • AI-powered tools for qualitative data analysis (e.g., transcription, summarization, thematic analysis)
  • conducting research with technical audiences (e.g., developers, data analysts, or engineers)
  • Basic coursework or project experience related to AI/ML or data processing

What the JD emphasized

  • AI Foundations organization
  • AI-driven tools and agentic systems
  • AI models, systems, and agents
  • AI development cycles
  • AI-powered tools