Human Factors Research Engineer, AIML Data Operations

Apple • Seattle, WA

1d

About The Position

Apple’s AIML Data Operations organization delivers high-quality, human-annotated machine-learning data at scale for product teams across Apple. It operates as both an operations team and a trusted partner in developing Apple’s consumer software and hardware experiences. Its global data annotation and collection initiative supports new experiences and flagship products such as Apple Intelligence and Vision Pro.

The Human Factors Research Engineer will conduct user experience research to optimize the design of annotation workflows and analyst tools that contribute to Apple’s strategic AI initiatives. The role involves evaluating user interface designs and applying mixed-methods research to improve these workflows and tools.

Requirements

• MS or PhD in Computer Science, Human-Computer Interaction, or an equivalent degree.
• At least 3 years of experience in mixed-methods human factors research, especially evaluating user interface designs.
• Expertise in qualitative and quantitative experimental design, statistical data analysis, and reporting.
• Excellent listening, communication, and interview skills in individual and focus group settings.
• Experience with human-in-the-loop evaluation, data annotation workflows, or AI/LLM model development.

Nice To Haves

• Proactive, curious, data-driven, and collaborative.
• Proficiency with data exploration and analysis languages or tools such as SQL, Python, or R Studio.
• Industry experience working with UX designers and software engineers to develop highly usable and performant interfaces.
• Published research in human-in-the-loop evaluation or data annotation workflows.

Responsibilities

• Conduct mixed-methods human factors research, especially to evaluate user interface designs.
• Research and help optimize the design of annotation workflows and analyst tools for Apple AI initiatives.
• Design experiments, analyze statistical data, and report findings.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level