Google

Staff UX Researcher, Agentic AI, Ad Sales and Marketing Platform

Google Mountain View, California, United States · $188K–$274K/yr

Software Development · 10,001+ employees

6 h ago
ux-researcher Senior (5-10 yrs) Full-time United States
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About the role

The role involves bridging user needs with business goals by transforming complex AI issues into actionable research questions. You will drive AI evaluation for Agentic systems and advise leadership on high-priority problems to ensure technical solutions address real-world human needs.

What they look for

Product Research Statistics Experimental Design Human-Computer Interaction Cognitive Science Psychology Anthropology Factorial Designs Linear Mixed-Effects Models R Python Psychometric Modeling Agentic AI Generative AI Machine Learning Project Management

Requirements

Candidates must have at least 8 years of product research experience and 5 years of experience in statistics and experimental design. A Bachelor's degree is required, while a Master's or PhD in a related field is preferred.

Benefits

Bonus Equity Health Insurance

Full description

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 8 years of experience in product research in an applied research setting,.
  • 5 years of experience in statistics, survey research, and the principles of experimental design.

Preferred qualifications:

  • Master's degree or PhD in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, or related fields.
  • 7 years of experience managing projects, and working in a large organization.
  • Expertise in multi-variable experimental methods, including factorial designs, within-subjects/repeated measures, and counterbalancing strategies (e.g., controlling for order and framing effects across multi-agent turns).
  • Advanced proficiency in linear mixed-effects models (LMMs/GLMMs) in R or Python, as well as psychometric and comparative scaling methods (e.g., IRT, Bradley-Terry, and Thurstonian modeling) for task-difficulty and rater-bias calibration.

About the job:

As a part of the tight-knit cross-functional team, the mission of Sales and Marketing Platform is to provide intelligence and assistance across a powerful platform that is responsible for the end-to-end life-cycle for all Google Ads customers. You will serve as Google’s single-front for global sales teams and supporting advertisers throughout the end-to-end life-cycle, Sales and Marketing Platform drive customer success, margin expansion, and seller effectiveness. You will operate at the unique intersection of Ads, GTech, and Global Business Organization (GBO)as the team fuels global customer growth through AI-driven innovation. You will be dedicated to developing highly effective AI agents and AI tools for sellers and advertisers, enabling them to achieve their goals and succeed in the current AI-driven landscape.Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.

Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $188000 - $274000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

  • Act as the bridge between user needs and business reality by identifying and clarifying leadership trade-offs to ensure product decisions are both user-centered and commercially viable.
  • Transform technical or ambiguous AI issues into actionable research questions and design recommendations.
  • Drive AI evaluation for Agentic AI systems.
  • Push the boundaries of what the team is currently considering for Agentic AI by advising Director-level and VP-level stakeholders and clarifying the highest-priority problems to solve.
  • Design and execute research to continuously ensure that complex technical solutions solve real-world human problems.

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