Senior Human-Centered AI Researcher, Personal Intelligence

Cupertino, California, United States Software and Services

At Apple, we create intuitive, intelligent experiences that enrich people's lives. We are seeking a Senior Human-Centered AI Researcher to help shape the next generation of software experiences across Apple's ecosystem. In this role, you will lead research that advances our understanding of how people interact with both emerging AI capabilities and established software experiences. Working closely with engineering, design, marketing, data science, and AI/ML modeling teams, you will define research strategies, uncover user needs and expectations, and translate behavioral insights into actionable recommendations that influence product direction, design, quality and ultimately shape the end customer experience.

Our team conducts human-centered research throughout the software and AI-feature development lifecycle, from understanding user needs and expectations to evaluating early prototypes and assessing product experience quality. We combine rigorous qualitative and quantitative methods to understand how people perceive, interact with, and experience software, including intelligent and adaptive systems.

The ideal candidate brings deep expertise in experimental design, statistical analysis, and mixed-methods research, with the scientific judgment to select and adapt methodologies to complex product questions. You will independently lead research initiatives across multiple product areas, collaborating with cross-functional partners to identify critical research questions, establish meaningful evaluation criteria, and translate findings into actionable product recommendations.

This role requires the ability to communicate complex findings to diverse audiences, including senior leadership and executives, and directly influence product strategy and development priorities. You will also contribute to research strategy, advance methodological practices, and mentor other researchers.

• Define and lead human-centered research strategies across multiple software and AI-powered experiences, identifying critical research questions and opportunities to inform product development.
• Design and execute rigorous qualitative, quantitative, and mixed-methods studies, including controlled experiments, surveys, usability evaluations, interviews, longitudinal studies, and Ecological Momentary Assessment (EMA).
• Apply experimental design principles and appropriate statistical techniques to evaluate user behavior, perceptions, expectations, and experience quality.
• Lead research throughout the software and AI-feature development lifecycle, from early user needs and expectations research through prototype evaluation, feature refinement, and product quality assessment.
• Develop human-centered evaluation frameworks, experience metrics, and success criteria to assess usability, usefulness, reliability, and perceived quality of software and intelligent systems.
• Partner closely with engineering, design, product marketing, data science, and AI/ML modeling teams to align research objectives with product and technical priorities, inform tradeoffs, and guide feature development.
• Integrate insights from qualitative research, self-reported measures, experimental data, and behavioral telemetry to develop a comprehensive understanding of user experience.
• Translate complex research findings into clear, compelling presentations and recommendations for cross-functional teams, senior leadership, and executives, directly influencing product direction and development decisions.
• Provide technical and methodological leadership across multiple projects, mentoring researchers, developing scalable research approaches, and advancing research practices across the organization.

• PhD in Cognitive Science, Experimental Psychology, Neuroscience, Human-Computer Interaction or a related field with substantial training in quantitative and qualitative research.
• 5+ years of relevant experience conducting human-centered research in technology or software product development.
• Formal training and demonstrated expertise in experimental design, including hypothesis development, study design, sampling strategies, randomization, measurement, and interpretation of experimental results.
• Strong proficiency in statistics including t-tests, analysis of variance (ANOVA), regression models, clustering techniques, factor analysis,…