Applied Scientist Intern, PhD (Summer 2027)

The role

You will develop next-generation user simulation methods using state of the art AI methods. You will build agent-based simulation systems grounded in real rider context and behavioral data to develop and validate LLM-based Rider Agents.

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

Required qualifications

• 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 working 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 and communicate with others to solve a problem
• 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
• Familiarity with prompting, tool use, memory, planning, or coordination in LLM-based agents
• Publication record in relevant venues such as NeurIPS, ICLR, AAAI, ICML or ACL/EMNLP
• Interest in building simulation platforms that support hypothesis generation, intervention testing, or human-AI system design

Benefits

• Medical, dental, and vision insurance options
• Mental health benefits
• 2 days paid time off
• 3 days sick time off
• 401(k) plan
• Subsidized commuter benefits
• Lyft Pink - exclusive opportunity to test new benefits of our Ridership Program

About the company

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.