PhD Research Scientist Intern
$157,000–$157,000 year
HybridSan Francisco, California, United States
Job Summary
Develop a synthetic data pipeline producing conversations with the design agent, conditioned on personas and statistical criteria derived from real usage. Combine persona-conditioned user-simulation techniques with existing intent-labeling and clustering pipelines to maintain synthetic output in-distribution with real usage. Measure realism gaps, distributional fit, and downstream evaluation quality using rigorous, reproducible validation. Collaborate with eval, labelling, research, and product teams to determine synthetic data substitution for real user-generated content. Contribute methodology and findings to the broader research community through publication where results support it. This 16-week full-time internship runs September through December, based in San Francisco with hybrid work options. You must be a current PhD student with experience in human-AI interaction and machine-learning experiments.
Required Qualifications
- Currently completing a PhD
- Experience with human-AI interaction, conversational agents, or user-modeling research
- Ability to design, run, and interpret machine-learning experiments with strong scientific rigour
- Ability to develop research code for data processing, model training, and evaluation
- Ability to communicate technical work clearly in writing and presentations
- Ability to collaborate effectively across teams
- Based in San Francisco
Desired Qualifications
- Ideally third year or later (PhD)
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