Applied Scientist Intern, PhD (Summer 2027)
Core
Develop LLM-based Rider Agents and agent-based simulation systems to serve as behavioral proxies for real riders and validate product interventions before online experimentation.
Role type
Applied Scientist Intern (PhD)
Builds
Rider Agent simulation prototype and evaluation framework
Domain
Transportation / AI / Behavioral Modeling
Deliverable
production ML models
Required skills
Python, Large Language Models, Agent-based modeling, Machine Learning, Causal inference, Empirical model evaluation, Prototyping
Preferred skills
Production ML inference pipelines, Generative user simulation, Computational social science, A/B testing, Prompting, Tool use, Memory, Planning
Technologies
Python, LLMs
Responsibilities
Develop LLM-based Rider Agents representing heterogeneous rider contexts; Build agent-based simulation environments for evaluating rider interactions; Build evaluation pipelines to assess realism and robustness; Analyze emergent behaviors in simulated populations; Conduct experiments and ablation studies on agent behavior; Apply simulation framework to real Rider product problems.
