Head of Population Simulation Research

About the role

The Head of Simulation Research at Aaru will set the research strategy, conduct original research, and lead a team of researchers. This is a hands-on research leadership role where the candidate will be a player-coach, choosing the bets to make, designing experiments, and recruiting exceptional people.

Responsibilities

• Define and continuously refine a coherent research agenda for individual behavior, group dynamics, and population-level validity.
• Choose a small number of high-leverage bets and establish the experiments, baselines, and decision criteria needed to evaluate them.
• Personally design and run experiments, build prototypes, analyze model behavior, and turn ambiguous findings into the next testable question.
• Develop new methods for agent construction, memory, interaction, behavioral calibration, population synthesis, and uncertainty estimation.
• Build evaluation frameworks that compare simulated behavior with real observations and reveal where apparent success does not generalize.
• Establish high standards for reproducibility, falsifiability, negative results, and honest communication of limitations.
• Partner closely with Simulation Engineering to hand off validated methods with evidence, implementation insight, known failure modes, and clear production hypotheses.
• Hire, mentor, and lead a small team of exceptional researchers and research engineers.

Requirements

Someone successful will have developed an original research agenda at a frontier ML lab or an environment with an equivalent bar for rigor and ambition. They will be equally comfortable forming a research strategy, designing an experiment, writing code, and inspecting individual failures. They will have led researchers or a major technical direction while remaining a direct contributor to the work. They can turn an important but poorly specified question into a sequence of decisive experiments. They care more about discovering the truth than preserving an elegant hypothesis or producing a persuasive demo. They can synthesize ideas across machine learning, behavioral science, statistics, economics, or complex systems without becoming trapped by one discipline’s conventions. They communicate results plainly to researchers, engineers, customers, and company leadership—including negative results and inconvenient limits.

Qualifications

Strong candidates may also have experience in multi-agent systems, LLM behavior, post-training, evaluation, synthetic environments, or model-based experimentation. They have worked in computational social science, behavioral modeling, economics, psychometrics, causal inference, or adjacent fields. Their research has changed a model capability, product decision, or scientific understanding—not merely a benchmark score. They have experience recruiting and mentoring unusually strong researchers and research engineers.

Skills

Successful candidates will have a strong background in machine learning, behavioral science, statistics, economics, or related fields. They will be skilled in designing and running experiments, building prototypes, analyzing model behavior, and developing new methods. They will have excellent communication skills and the ability to synthesize ideas across different disciplines.

Benefits

Full benefits package including health insurance, retirement savings plan, and paid time off.

Pay

Base salary of $425,000–$525,000, equity, and full benefits. Final compensation depends on experience and sits within our internal bands.

Schedule

This is a full-time position requiring five days a week in-person work in New York City.