• Design and advance methods for synthesizing realistic agents from structured and unstructured profile data
• Build and evaluate simulation pipelines that produce population-level distributional accuracy across demographic, attitudinal, and behavioral dimensions
• Develop techniques for grounding agent behavior in real-world data sources — surveys, behavioral traces, psychometric instruments, and domain-specific datasets
• Design hybrid architectures that combine large language models with classical methods from computational social science, psychometrics, and survey methodology
• Build rigorous evaluation frameworks that measure simulation quality against known ground-truth distributions (e.g., GSS, census, proprietary panel data)
• Identify and close gaps between simulated and observed population behavior through iterative experimentation

YOU MAY BE A FIT IF

• You have deep experience with synthetic data generation, agent-based modeling, computational social science, or population simulation
• You are interested in using LLMs as a simulation substrate — not just for text generation, but for producing structured behavioral outputs that hold up under statistical scrutiny
• You think carefully about what it means for a simulation to be "accurate" and can articulate the difference between individual-level plausibility and distributional fidelity
• You have a PhD in ML, computational social science, cognitive science, statistics, psychometrics, or a quantitative field — or equivalent depth from industry research
• You communicate clearly about what's working and what isn't, including when results are null or ambiguous
• You move fast and are comfortable producing work at high velocity without sacrificing rigor

STRONG CANDIDATES MAY ALSO

• Have built systems that generate or evaluate synthetic populations at scale
• Have experience with survey methodology, psychometrics, or demographic modeling
• Have published work on agent-based simulation, synthetic data, or LLM-based behavioral modeling
• Have worked in a high-velocity research environment where shipping matters as much as rigor

LOCATION

This role is based in New York City. This is an in-person company and during this exciting period of hypergrowth, we work 6 days a week in office. Candidates are expected to be located within the New York City metropolitan area or open to relocation.

BENEFITS

We take care of our people. In addition to a competitive base salary and equity participation, we offer comprehensive medical, vision, and dental coverage, visa sponsorship and relocation support, and various other benefits and perks.