About this role
Developing next-generation user simulation methods using advanced artificial intelligence approaches forms the core day-to-day focus for this internship. The Rider Science team at Lyft builds and validates large language model-based rider agents that serve as behavioral proxies for real users, helping teams evaluate product interventions before running online experiments. This summer role involves constructing agent-based simulation systems grounded in historical data and real rider context, evaluating simulation fidelity, and assessing how these models can accelerate product iteration.
Candidates pursuing a PhD in Computer Science or a related technical field who possess a strong foundation in machine learning, Python proficiency, and hands-on experience with large language models or agent-based systems will thrive in this environment. The position exists to help researchers study when agent simulations provide reliable signals for product development, bridging the gap between theoretical modeling and practical transportation applications.
What you will do
- Develop LLM-based Rider Agents that represent heterogeneous rider contexts, preferences, histories, and behaviors.
- Build agent-based simulation environments for evaluating rider interactions with different product experiences and interventions.
- Build evaluation pipelines to assess realism, robustness, and mechanism plausibility of simulated behavior against human data or established 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 and assess its usefulness for hypothesis generation, product iteration, and pre-experiment evaluation.
- Communicate technical findings and recommendations to science, engineering, and product partners.
What you need
- 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.
- Demonstrate proficiency with Python and working in a production coding environment.
- Bring hands-on experience with large language models or agent-based systems.
- Possess a strong foundation in machine learning and empirical model evaluation.
- Demonstrate the ability to independently develop prototypes and work through open-ended technical problems.
- Exhibit strong verbal and written communication skills, along with the ability to collaborate with others to solve problems.
- Maintain familiarity with A/B testing, causal inference, or experimental design.
Nice to have
- Experience building production level ML inference, simulation, or evaluation pipelines
- Prior research experience with LLM agents, generative user simulation, or agent-based modeling
- Background in computational social science or behavioral modeling
- Experience evaluating AI systems against human behavioral data, qualitative studies, or controlled experiments
- Publication record in relevant venues such as NeurIPS, ICLR, AAAI, ICML or ACL/EMNLP
Benefits
- Great medical, dental, and vision insurance options
- Mental health benefits
- 2 days paid time off and 3 days sick time off for interns
- 401(k) plan to help save for your future
- Subsidized commuter benefits
- Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
Skills and tech stack
Questions candidates ask
What is the remote or in-office policy for this role?
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule where team members are expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays.
What is the expected compensation for this position?
The expected base pay range for this position in the San Francisco area is $64-$68/hour. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location.
What are the educational requirements for this internship?
Candidates must be currently pursuing a PhD degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related technical field. The expected graduation date must be between December 2027 and Summer 2028.