Find & Apply For UI / UX Designer / Developer Jobs in Burlingame, California

Our UX Research team is designing for businesses of all shapes and sizes, which requires us to better understand the customers who use our platform. Our researchers tackle some of the most complex challenges to gain valuable insights into how advertisers interact with our tools and platform, and work collaboratively to contribute new ideas to products that impact the experiences of millions of businesses on a global scale. This job description represents different full-time roles across Meta. We use a variety of qualitative and quantitative methods to accomplish our goals, including surveys, focus groups, field studies, usability tests, and 1:1 interviews. We value different perspectives and stem from many different backgrounds. We're looking for skilled communicators who are knowledgeable about research devoted to understanding people, and curious about the relationship between technology and society.

Qualifications:

Bachelor's degree with 4+ years of relevant experience within user experience, applied research setting and/or product research and development, Master's degree and 2+ years relevant experience, or a PhD and relevant experience Experience conducting In-Depth Interviews or Focus Groups and Concept Testing or Usability Testing Interest in and experience executing hands-on, primary research Experience translating research findings into strategic narratives Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Degrees in a human behavior related field, such as Human-Computer Interaction, Psychology, Sociology, Communication, Information Science, Media Studies, Computer Science, or Economics Experience with advertising industry, digital marketing product development Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)