Research Scientist (AI)

Location: San Francisco, United States; hybrid work

Salary: $200K–$240K per year, plus equity

Company

hirify.global develops AI-powered user interviews and digital twins that represent specific people and respond to research questions like those people would.

What you will do

• Co-design and run qualitative and quantitative studies comparing system-generated responses with responses from humans.
• Design, justify, and refine performance measures and apply statistical techniques from survey methodology and large-scale social data analysis.
• Design evaluations and experiments with pre-specified analysis plans, including human rating studies, rater training, coding rubrics, and inter-rater agreement measurement.
• Design data collection from third-party sources and human participants, including longitudinal and repeated-measures studies.
• Contribute to research on new modeling approaches, including fine-tuned models and model calibration.
• Specify analyses precisely enough for implementation by engineers and co-author papers, preprints, and presentations.

Requirements

• Completed or nearly completed PhD in computational social science, communication, HCI, sociology, political science, psychology, statistics, or a related field.
• Primary-author peer-reviewed publications.
• Working command of graduate-level statistical methodology used in social science, including the assumptions behind each method.
• Experience analyzing large-scale telemetry and behavioral datasets while assessing the validity of resulting inferences.
• Familiarity with machine learning, including classical, nonparametric, and LLM-based approaches; transformer language models, fine-tuning, and differences between major model families.
• Fundamentals of computing, including file systems, software libraries, databases, SQL, and tabular data.
• Ability to work in an environment where most code is produced through agentic coding tools and to read and check that code.

Nice to have

• Experience fine-tuning open-weight language models on survey, experimental, or behavioral data.
• Experience building or evaluating calibrated confidence or error-prediction models, including deriving decision thresholds from human judgments.
• Experience measuring open-ended text similarity, including embedding-based methods.
• Experience designing or running panel-based data collection with human participants.
• Experience presenting research at academic or industry conferences.
• Prior work with generative agents, digital twins, or simulation of human respondents.
• Familiarity with the startup ecosystem, qualitative interviews, ethnographic methods, and computational linguistics.

Culture & Benefits

• Hybrid work in San Francisco.
• Opportunity to work on AI-moderated research and digital-twin systems for enterprise customers.
• Compensation includes equity.