UX Research Scientist Intern, Multimodal Conversation Analyst (PhD)

📍 Job Overview

Job Title: UX Research Scientist Intern, Multimodal Conversation Analyst (PhD) Company: Meta Location: Redmond, WA Job Type: INTERN Category: Research & Development / Data Science / Human-Computer Interaction Date Posted: November 25, 2025 Experience Level: 0-2 Years (Internship Level) Remote Status: On-site

🚀 Role Summary

• This internship focuses on applied empirical research within Meta Reality Labs, specifically investigating complex social and relational communication contexts.
• The role involves leveraging machine perception data (egocentric, multimodal) to build representations of user state and social dynamics for next-generation AI wearables, VR, and AR devices.
• Candidates will design, execute, and analyze research using both qualitative and quantitative social science methodologies, with a strong emphasis on understanding human experience through rich behavioral datasets.
• The position is ideal for PhD candidates whose research interests align with interpersonal communication, language and social interaction, communication technologies, and computational social science.

📝 Enhancement Note: This is an internship role, indicated by "INTERN" employment type and "0-2 Years" experience level. The "On-site" remote status and specific location in Redmond, WA, are critical for candidates considering relocation or local employment. The focus on "Multimodal Conversation Analyst" and "UX Research Scientist" suggests a blend of social science rigor and human-computer interaction principles applied to conversational AI and immersive technologies.

📈 Primary Responsibilities

• Plan and execute cutting-edge research and development projects to advance the state-of-the-art in machine perception for social interaction analysis.
• Collaborate closely with a world-class team of researchers and engineers across Meta's machine perception and AI development groups.
• Design, set up, and conduct practical experiments and analyses focused on large-scale, high-quality sensing and machine reasoning for representing social and behavioral primitives.
• Take ownership of research projects end-to-end, including navigating project trade-offs, proposing appropriate methodologies, analyzing complex datasets, and communicating findings to diverse audiences (technical and non-technical).
• Contribute to the development of AI systems that understand and facilitate human communication in personal, professional, and community settings, both online and offline.

📝 Enhancement Note: The responsibilities emphasize end-to-end research ownership, a common expectation for advanced interns and junior researchers. The focus on "social and behavioral primitives" and "machine perception" indicates a deep dive into analyzing nuanced human interactions from sensor data. Collaboration with "machine perception teams at Meta" suggests integration with core technology development.

🎓 Skills & Qualifications

Education:

• Currently pursuing a PhD in Human-Computer Interaction, Linguistics, Cognitive Science, Computer Science, Psychology, or a closely related field with a specific focus on social interaction or pragmatic language analysis.
• 📝 Enhancement Note: The requirement for a PhD candidate is paramount, indicating a need for advanced theoretical understanding and research capabilities. The specific fields listed highlight the interdisciplinary nature of the role.

Experience:

• Demonstrated experience in computer-assisted analysis of language use, encompassing both qualitative (e.g., conversation analysis, discourse analysis) and quantitative methods.
• Proficiency in Python and/or R for data analysis, including practical experience with relevant libraries such as NLTK, spaCy, pandas, and scikit-learn.
• Experience working with specialized datasets, including but not limited to: social interaction recordings (audio/video), interview transcripts, device telemetry logs, and various sensor streams (e.g., gaze tracking, gesture recognition, physiological data).
• Familiarity with machine perception models capable of inferring user attention, object handling, and interaction patterns from multimodal data.
• Ability to design and implement robust data collection protocols for behavioral and sensor data.
• Must obtain work authorization in the country of employment at the time of hire and maintain it throughout the internship.

Required Skills:

• Human-Computer Interaction (HCI) principles and research methodologies.
• Linguistics, with a focus on Pragmatic Language Analysis and Social Interaction.
• Qualitative and Quantitative Research Methods (e.g., Conversation Analysis, Discourse Analysis, statistical analysis).
• Data Analysis and Statistical Modeling using Python or R (NLTK, spaCy, pandas, scikit-learn).
• Machine Perception concepts and their application to understanding user behavior.
• Experience with Multimodal Data analysis (audio, video, sensor streams).
• Behavioral Data collection and interpretation.

Preferred Skills:

• Hands-on experience integrating and analyzing multimodal datasets, specifically combining behavioral, linguistic, and device-derived sensor streams.
• Experience with self-reported measures of cognitive load, stress, emotional valence, and arousal, and their integration with objective sensor data.
• A strong track record of publishing research in top-tier conferences or journals within fields such as social interaction, language technology, or human behavior analysis.
• Experience developing or applying machine learning models to infer social, cognitive, or emotional states from complex, real-world data.
• Familiarity with tools and techniques for synchronizing and annotating multimodal data (e.g., ELAN, Praat, custom annotation pipelines).
• Demonstrated ability to work collaboratively in interdisciplinary teams, effectively communicating complex findings to both technical and non-technical audiences.
• Intent to return to one's degree program after the completion of the internship.

📝 Enhancement Note: The required skills strongly emphasize a blend of social science research expertise (linguistics, psychology, HCI) and computational skills (Python/R, NLP, ML). The preferred skills point towards candidates who have already engaged in high-level research, evidenced by publications and experience with advanced data integration and analysis techniques. The explicit mention of returning to a degree program is standard for internships.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Demonstrate end-to-end research project lifecycle, from problem definition and methodology design to data analysis and impactful communication of findings.
• Showcase experience with data collection, including the design and implementation of protocols for behavioral and sensor data.
• Highlight proficiency in analyzing complex, multimodal datasets, with examples of how qualitative and quantitative methods were integrated.
• Present evidence of working with specialized datasets such as social interaction recordings, interview transcripts, or device telemetry.
• 📝 Enhancement Note: For an internship, the portfolio should focus on academic research projects, thesis work, or significant class projects that demonstrate the core competencies. The emphasis is on research process and analytical rigor rather than commercial product development.

Process Documentation:

• Examples of research proposals outlining clear research questions, hypotheses, and proposed methodologies.
• Documentation of data analysis workflows, including code repositories (e.g., GitHub) demonstrating Python/R script usage for data manipulation, analysis, and visualization.
• Case studies of how complex research findings were translated into actionable insights for diverse audiences.
• Protocols or guidelines developed for data collection, annotation, or synchronization of multimodal data.
• 📝 Enhancement Note: The portfolio should clearly articulate the "how" behind the research, not just the "what." Demonstrating structured thinking in research design and execution is key.

💵 Compensation & Benefits

Salary Range:

• As an internship position at Meta, compensation will be competitive and reflective of the candidate's academic standing (PhD candidate), location (Redmond, WA), and the specialized nature of the role. While specific figures are not provided, typical intern salaries for PhD candidates in major tech hubs like Seattle/Redmond can range from $6,000 to $10,000+ per month, plus potential housing stipends or relocation assistance.
• 📝 Enhancement Note: This estimate is based on industry benchmarks for PhD internships at top technology companies in the Seattle metropolitan area. Actual compensation will be confirmed by Meta during the offer stage and may vary based on specific start dates and duration.

Benefits:

• Competitive monthly stipend.
• Housing assistance or stipend.
• Relocation assistance for eligible candidates.
• Access to Meta's campus facilities and amenities (e.g., dining, fitness centers, recreational spaces).
• Opportunities for networking and professional development with leading researchers and engineers.
• Exposure to cutting-edge research in VR, AR, and AI.
• 📝 Enhancement Note: Benefits for internships often focus on supporting the intern's ability to focus on research and integrate into the company culture, rather than long-term employee benefits.

Working Hours:

• Standard internship hours are typically 40 hours per week, Monday through Friday.
• Flexibility may be offered around specific project needs or academic commitments, subject to team and manager approval.
• 📝 Enhancement Note: While a standard 40-hour week is expected, the research-oriented nature of the role might allow for some flexibility in scheduling, especially for PhD candidates managing their academic progress.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology (Social Media, Virtual Reality, Augmented Reality, Artificial Intelligence) Company Size: Large Enterprise (Meta Platforms, Inc. employs over 60,000 people globally). Founded: 2004 (Meta Platforms, Inc.) Team Structure:

• The Reality Labs Research team is a highly specialized group of scientists and engineers focused on pioneering the future of immersive technologies and AI.
• Interns typically work within specific research pods or project teams, reporting to a dedicated research mentor.
• Collaboration is highly interdisciplinary, involving researchers from HCI, computer vision, machine learning, natural language processing, linguistics, psychology, and social sciences.

Methodology:

• The team employs a rigorous, data-driven research methodology, combining theoretical frameworks with empirical validation.
• Emphasis is placed on scientific inquiry, hypothesis testing, and iterative experimentation.
• Agile principles may be applied to research project management, allowing for adaptability and rapid iteration based on findings.

Company Website: https://www.metacareers.com/

📝 Enhancement Note: Meta's culture, particularly within Reality Labs Research, is characterized by ambitious goals, a fast-paced environment, and a strong emphasis on innovation and scientific rigor. Interns are expected to contribute meaningfully and are integrated into ongoing research efforts.

📈 Career & Growth Analysis

Operations Career Level: This is an internship role, specifically for a PhD candidate. It serves as a foundational experience for individuals aspiring to careers in applied research, particularly at the intersection of AI, HCI, and social sciences. Reporting Structure: Interns typically report to a Research Scientist or Research Manager who acts as their mentor, guiding their project and professional development during the internship. They will also work closely with other team members. Operations Impact: While not a traditional "operations" role, the research conducted directly impacts the future development of Meta's products and technologies. Insights gained from analyzing user behavior and conversation dynamics are crucial for designing more intuitive, engaging, and socially intelligent AI systems and immersive experiences.

Growth Opportunities:

• Skill Development: Deepen expertise in multimodal data analysis, advanced qualitative/quantitative research methods, and specific areas of linguistics or social psychology relevant to communication.
• Networking: Build connections with leading researchers and potential future employers in the tech industry.
• Publication Potential: Opportunity to contribute to research that may lead to publications in top-tier academic venues.
• Industry Exposure: Gain firsthand experience in a leading AI research lab, understanding the challenges and opportunities in developing next-generation technologies.
• Career Exploration: Evaluate career paths in applied research within major technology companies.

📝 Enhancement Note: This internship is a significant stepping stone for academic researchers looking to transition into industry research roles. The experience gained, especially if it leads to publications or strong project outcomes, can be highly valuable for future academic or industry positions.

🌐 Work Environment

Office Type: The role is on-site at Meta's facilities in Redmond, WA. This implies a modern, well-equipped office environment designed for collaboration and research. Office Location(s): Redmond, Washington, USA. This location is part of the greater Seattle tech hub, offering a vibrant ecosystem for technology and research professionals.

Workspace Context:

• Interns will have access to dedicated workspace, likely with high-performance computing resources necessary for data analysis and model development.
• The environment fosters collaboration through shared spaces, meeting rooms, and informal interaction areas.
• Access to specialized research equipment and software relevant to machine perception, data collection, and analysis will be provided.

Work Schedule:

• The standard work schedule is typically Monday to Friday, 9 AM to 5 PM, with potential for some flexibility.
• The focus is on achieving project milestones and contributing to research goals within the internship period.

📝 Enhancement Note: Working on-site at Meta provides immersion in a cutting-edge research environment, facilitating direct collaboration and access to resources that may not be available elsewhere. The Redmond location places the intern within a significant technology corridor.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Application and resume review to assess academic background, research experience, and alignment with minimum qualifications.
• Technical/Research Interview(s): Typically involves one or more interviews with Research Scientists or Managers. These will focus on:
  • Deep dives into past research projects (academic thesis, publications, significant class projects).
  • Discussions on research methodologies, data analysis techniques, and problem-solving approaches.
  • Assessment of familiarity with required tools (Python/R, NLP libraries) and concepts (machine perception, social interaction analysis).
  • Scenario-based questions to evaluate critical thinking and research design capabilities.
• Portfolio Review (if requested): Candidates may be asked to present specific projects from their portfolio, elaborating on their role, methodologies, findings, and impact.
• Final Round: May involve meeting with additional team members or a senior researcher to assess fit and discuss project alignment.

Portfolio Review Tips:

• Curate Select Projects: Choose 2-3 projects that best showcase your skills in multimodal data analysis, social interaction research, and quantitative/qualitative methods.
• Structure Your Narrative: For each project, clearly articulate:
  • The research problem and its significance.
  • Your specific role and contributions.
  • The methodologies employed (why you chose them).
  • Key findings and their implications.
  • Challenges faced and how you overcame them.
  • Any potential for future research or product impact.
• Demonstrate Technical Proficiency: Be prepared to discuss your code, data analysis pipelines, and the specific libraries or tools you used.
• Highlight Communication Skills: Practice explaining complex technical and research concepts clearly and concisely, tailoring your explanation to the interviewer's background.
• Show Enthusiasm for Meta's Mission: Connect your research interests to Meta's work in Reality Labs and its vision for the future of human-computer interaction.

Challenge Preparation:

• Be ready for hypothetical research design questions. For instance, "How would you study X phenomenon using Y data?" or "What are the ethical considerations for collecting Z type of data?"
• Prepare to discuss trade-offs in research design (e.g., sample size vs. data richness, qualitative depth vs. quantitative breadth).
• Review foundational concepts in conversation analysis, pragmatics, and HCI.

📝 Enhancement Note: The interview process for a PhD internship at Meta is rigorous and expects candidates to demonstrate a strong foundation in research principles and practical analytical skills. A well-prepared portfolio that clearly articulates research contributions is crucial.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python (with libraries like NLTK, spaCy, pandas, scikit-learn), R.
• Data Analysis & Visualization: Pandas, NumPy, Matplotlib, Seaborn, SciPy, potentially specialized statistical packages.
• Machine Learning: Scikit-learn, TensorFlow, PyTorch (for ML model development and application).
• Annotation Tools (Preferred): ELAN, Praat, or custom annotation pipelines for synchronizing and labeling multimodal data.

Analytics & Reporting:

• Internal Meta tools for data processing, experimentation, and reporting (specifics are proprietary but generally align with industry standards for large-scale data analysis).
• Tools for statistical analysis and hypothesis testing.

CRM & Automation:

• Not directly applicable to this research intern role, as the focus is on research execution rather than sales or marketing operations. However, understanding how user data is managed and potentially automated within larger systems might be relevant context.

📝 Enhancement Note: Proficiency in Python and R for data analysis is a non-negotiable requirement. Familiarity with ML frameworks and specific annotation tools is highly advantageous. The role implies working with large, complex datasets, thus experience with efficient data handling and processing is key.

👥 Team Culture & Values

Operations Values:

• Impact-Driven Research: Focus on conducting research that has the potential to shape future technologies and user experiences.
• Scientific Rigor: Commitment to sound methodologies, objective data analysis, and evidence-based conclusions.
• Collaboration: Valuing teamwork, knowledge sharing, and interdisciplinary approaches to problem-solving.
• Innovation: Encouraging creativity, exploring novel ideas, and pushing the boundaries of what's possible in AI and immersive technologies.
• User-Centricity: Deeply understanding user needs, behaviors, and experiences to inform research and development.

Collaboration Style:

• Highly collaborative, with regular team meetings, research syncs, and cross-functional discussions.
• Emphasis on constructive feedback and open communication to refine research ideas and approaches.
• Interns are expected to actively participate in team discussions and contribute to a positive, intellectually stimulating environment.

📝 Enhancement Note: Meta's research culture emphasizes ambitious goals and a collaborative spirit. Interns are encouraged to be proactive, engage with the team, and contribute to the collective knowledge base.

⚡ Challenges & Growth Opportunities

Challenges:

• Data Complexity: Working with large, noisy, and multimodal datasets requires sophisticated analytical techniques and robust data cleaning processes.
• Interdisciplinary Integration: Bridging the gap between social science theories and computational methods can be challenging.
• Defining "Social Primitives": Quantifying and representing abstract social and behavioral concepts from sensor data is an inherently difficult research problem.
• Pace of Innovation: Keeping up with the rapid advancements in AI and immersive technologies requires continuous learning.

Learning & Development Opportunities:

• Mentorship: Receive guidance from experienced Research Scientists on research design, execution, and career development.
• Skill Enhancement: Opportunity to gain practical experience with state-of-the-art tools and techniques in machine perception, NLP, and HCI research.
• Industry Exposure: Learn about the product development lifecycle and research-to-product translation process at a leading tech company.
• Networking: Connect with a global network of researchers and engineers within Meta and the broader tech community.

📝 Enhancement Note: The challenges presented are typical for advanced research roles in cutting-edge technology fields. The growth opportunities are significant, offering a chance to learn from the best and contribute to impactful projects.

💡 Interview Preparation

Strategy Questions:

• Research Design: "Imagine you have access to egocentric video and audio data from conversations. How would you quantitatively measure the level of social rapport between participants?" (Focus on defining metrics, potential statistical models, and data processing steps).
• Methodology Justification: "You're considering using conversation analysis versus a purely NLP-based approach to understand conversational turn-taking. What are the pros and cons of each, and how would you decide which to prioritize for a specific research question?" (Demonstrate understanding of qualitative vs. quantitative strengths and weaknesses).
• Problem Solving: "A key sensor stream for your project is consistently noisy and intermittent. What steps would you take to mitigate this issue, both in terms of data processing and potentially in refining your research questions?" (Showcase practical data wrangling and adaptive research skills).

Company & Culture Questions:

• "Why are you interested in Meta Reality Labs specifically, and how does your research align with our goals in VR/AR and AI?" (Connect your personal research vision to Meta's stated mission).
• "Describe a time you had to collaborate with individuals from different technical or disciplinary backgrounds. What challenges did you face, and how did you overcome them?" (Highlight your interdisciplinary collaboration skills).
• "How do you approach ethical considerations in research involving human participants and sensitive data?" (Demonstrate awareness of ethical research practices).

Portfolio Presentation Strategy:

• Be Concise and Clear: Focus on the core research contributions and impact. Avoid getting lost in minor technical details unless specifically asked.
• Visual Aids: Use well-designed slides with clear visualizations of data, models, or workflows to support your narrative.
• Quantify Impact: Whenever possible, use metrics to demonstrate the significance of your findings or the efficiency of your methods.
• Storytelling: Frame your projects as compelling stories with a clear beginning (problem), middle (research journey), and end (results and implications).
• Anticipate Questions: Think about potential follow-up questions regarding your methodology, data limitations, and future research directions.

📝 Enhancement Note: Interview preparation should focus on demonstrating a strong research mindset, technical competence, and the ability to articulate complex ideas clearly. Be ready to defend your methodological choices and discuss the broader implications of your work.

📌 Application Steps

To apply for this operations position:

• Submit your application through the Meta Careers portal link provided.
• Resume Optimization: Tailor your resume to highlight experience in HCI, linguistics, social science research methods, Python/R programming, and any work with multimodal or sensor data. Quantify achievements where possible (e.g., "Analyzed X dataset using Y method to achieve Z insight").
• Portfolio Preparation: Assemble a digital portfolio (e.g., PDF, personal website, GitHub) showcasing your strongest academic research projects. Ensure it clearly details your research questions, methodologies, data analysis, and findings. Include links to relevant publications or code repositories if applicable.
• Interview Practice: Rehearse explaining your research projects using the STAR method (Situation, Task, Action, Result) and prepare to discuss your technical skills and research interests in detail. Practice articulating your thought process for research design challenges.
• Company Research: Familiarize yourself with Meta Reality Labs' current projects, research areas, and overall mission. Understand how your specific research interests contribute to their long-term vision.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.