Applied Scientist Intern, PhD (Summer 2027)

What you'll do

• Build Rider Agents, simulation environments, and evaluation pipelines grounded in rider data.
• Test simulation fidelity and analyze simulated behaviors across rider segments and marketplace conditions.
• Apply simulations to rider product problems and communicate findings to science, engineering, and product partners.

What they ask for

• Currently pursuing a PhD in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related technical field, with graduation between December 2027 and Summer 2028.
• Proficiency with Python and working in a production coding environment.
• Hands-on experience with large language models or agent-based systems, and a strong foundation in machine learning and empirical model evaluation.
• Ability to independently develop prototypes and communicate and collaborate effectively; familiarity with A/B testing, causal inference, or experimental design.

Nice to have

• Experience building production-level ML inference, simulation, or evaluation pipelines; research in LLM agents, generative user simulation, or agent-based modeling.
• Experience evaluating AI systems against human behavioral data or controlled experiments; relevant publications or familiarity with LLM agent prompting, tools, memory, planning, or coordination.

Pay

$64-$68/hour USD base salary

Tools

Python, LLMs

AI focus

Develop and evaluate LLM-based Rider Agents that simulate rider behavior and assess whether simulations can inform product interventions before online experiments.