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About the Role

The Lyft Rider Science team is seeking an Applied Scientist intern to develop next-generation user simulation methods using state-of-the-art AI. The goal is to create and validate LLM-based Rider Agents as behavioral proxies for real riders, studying their reliability in predicting responses to product interventions before online experimentation.

Responsibilities

Develop LLM-based Rider Agents representing heterogeneous rider contexts, preferences, histories, and behaviors.
Build agent-based simulation environments for evaluating rider interactions with product experiences and interventions.
Construct evaluation pipelines to assess the realism, robustness, and mechanism plausibility of simulated behavior against human data or theory.
Analyze emergent behaviors and interaction dynamics in simulated populations under different user segment and marketplace conditions.
Conduct experiments and ablation studies on agent behavior, interaction dynamics, and simulation validity.
Apply the simulation framework to real Rider product problems, assessing its usefulness for hypothesis generation, product iteration, and pre-experiment evaluation.
Communicate technical findings and recommendations to science, engineering, and product partners.

Requirements

Currently pursuing a PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related technical field, with a graduation date between December 2027 and Summer 2028.
Proficiency with Python and experience in a production coding environment.
Hands-on experience with large language models or agent-based systems.
Strong foundation in machine learning and empirical model evaluation.
Ability to independently develop prototypes and work through open-ended technical problems.
Strong verbal and written communication skills, and ability to collaborate effectively.
Familiarity with A/B testing, causal inference, or experimental design.

Skills

Python
Large language models
Agent-based systems
Machine learning
Empirical model evaluation
A/B testing
Causal inference
Experimental design
LLM engineering
Agent-based modeling
Prompting
Tool use
Memory
Planning
Coordination in LLM-based agents

Location

San Francisco area

Work Type

Hybrid
In-office

Experience Level

Internship
PhD student

Education Level

Salary/Compensations

$64-$68/hour

Benefits

Medical, dental, and vision insurance
Mental health benefits
2 days paid time off
3 days sick time off
401(k) plan
Subsidized commuter benefits
Lyft Pink membership

About the Company

Lyft's purpose is to serve and connect.
Lyft fosters a work environment where all team members belong and have the opportunity to thrive.
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture.

Equal Opportunity

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law.
We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.