Join Lyft as an Applied Scientist Intern to develop AI-driven user simulation methods for rider behavior analysis.
Posted by employer 1 day ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
Skills & Technologies
What you'll build
Must have
Nice to have
Practical constraints
AI in the day-to-day
Develop and validate LLM-based Rider Agents for simulating rider behavior.
Requirements
Not disclosed in this posting: years of experience, visa sponsorship.
Benefits
Joblaze summary
The Applied Scientist Intern at Lyft focuses on developing advanced user simulation methods, specifically creating LLM-based Rider Agents that mimic real rider behaviors. This role requires proficiency in Python and experience with machine learning, particularly in agent-based modeling and causal inference. It is well-suited for PhD candidates in relevant fields who can tackle complex technical challenges independently. The position is part of a collaborative team environment, emphasizing hands-on experimentation and product iteration.
Joblaze insights
Quick facts
From the original posting
The Lyft Rider Science team is seeking an Applied Scientist intern to develop next-generation user simulation methods using state of the art AI methods. The goal of this project is to develop and validate LLM-based Rider Agents that can serve as behavioral proxies for real riders, and study when agent simulations can provide reliable signal about rider responses to product interventions before online experimentation.
You will build agent-based simulation systems grounded in real rider context and behavioral data, evaluate their fidelity against observed rider behavior and historical experiments, and study where these simulations can accelerate product iteration and experimentation.
This role combines LLM engineering, agent-based modeling, machine learning, and causal inference with direct applications to real-world rider products. The expected outcome is to build a working Rider Agent simulation prototype, establish an evaluation framework for measuring simulation fidelity and validate the framework using historical rider experiments.
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 — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers.
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. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
Total compensation is dependent on a variety of factors, including qualifications, experience, and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
Standard company text repeated across Lyft's postings is omitted here.