Computational Behavioral Modeling Machine Learning Engineer

This is a remote, project-based role for machine learning researchers and engineers with deep expertise in computational modeling of human and animal behavior. You will complete tasks at the intersection of ML and behavioral science — including model development, behavioral data analysis, and research tasks applied to decision-making, cognitive modeling, social dynamics, and agent-based simulations of behavior. Work is over the next 2–3 weeks, asynchronous, and assigned on a project-by-project basis, with an expected commitment of 10–20 hours per week for the projects you accept. This position offers exceptional pay, exposure to cutting-edge behavioral ML research, and a strong addition to your research portfolio.

Responsibilities

• Apply machine learning techniques to behavioral modeling tasks including decision-making inference, cognitive process modeling, social behavior prediction, and agent-based simulation
• Build and evaluate computational models of behavior using reinforcement learning, Bayesian inference, and deep learning approaches
• Develop and fit models to behavioral datasets from human experiments, animal studies, or large-scale observational data
• Conduct rigorous model comparison and validation against behavioral benchmarks and cognitive theory
• Document methodologies, experimental results, and technical approaches clearly and reproducibly

Required qualifications

• Published researcher with at least one first-author publication in a peer-reviewed venue (e.g., NeurIPS, ICML, Psychological Review, Cognitive Science, PNAS, or equivalent)
• Master's or PhD in Computational Neuroscience, Cognitive Science, Psychology, Computer Science, or a related quantitative field
• Demonstrated expertise in both machine learning and computational behavioral modeling (e.g., reinforcement learning models of behavior, Bayesian cognitive models, or social simulation)
• Strong problem-solving skills and ability to work independently on technical and research tasks

Preferred qualifications

• Hands-on experience with behavioral modeling frameworks and tools (e.g., hBayesDM, HDDM, PyMC, or similar)
• Familiarity with large-scale behavioral datasets from online experiments, ecological momentary assessment, or digital phenotyping
• Experience with inverse reinforcement learning, theory of mind modeling, or multi-agent behavioral simulation
• Background in TA'ing or teaching cognitive science, computational neuroscience, or machine learning courses

Why apply

• Flexible Time Commitment – Work on your schedule while tackling meaningful research challenges
• Startup Exposure – Work directly with an early-stage Y Combinator-backed company, gaining hands-on experience that sets you apart
• Exceptional Pay – Project-based pay ranges from $150–$200/hour
• Portfolio Building – Gain experience applying ML to frontier computational behavioral modeling problems
• Professional Growth – Sharpen your skills on varied, challenging behavioral datasets and cognitive models