Staff UX Researcher, GeminiApp, DeepMind

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $252000 - $274000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Identify the next wave of user needs in generative AI. Move beyond tactical testing to lead foundational research that informs the multi-year product roadmap.
• Define the signals used for model tuning Reinforcement Learning from Human Feedback (RLHF) to ensure the AI’s personality and reasoning align with user expectations.
• Partner with Research, Product Management, and Strategy and Operations to integrate user insights into the core business and technical strategy.
  
• Develop and scale new frameworks for evaluating AI. You will pioneer ways to measure complex concepts like hallucination tolerance, creative agency, and collaborative trust that traditional UX metrics often miss.

Minimum qualifications:

• Bachelor's degree in Human-Computer Interaction, Psychology, Cognitive Science, or a related field, or equivalent practical experience.
  
• 8 years of experience in User Experience Research, Product Strategy, or a related field within consumer-facing technology.
  
• Experience in qualitative and quantitative research methods.

Preferred qualifications:

• Experience working on systems (e.g., AI, search, algorithmic feeds, or cloud platforms) where the user experience is driven by machine learning.
• Experience influencing executive stakeholders and managing product changes through evidence-based narratives.