Applied Scientist Intern

Who you are

• 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 (required)
• 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
• 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

What the job involves

• 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

Benefits

• Great medical, dental, and vision insurance options
• Mental health benefits
• In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
• 401(k) plan to help save for your future
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Pre-tax commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program
• Family building benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program