# Applied Scientist Intern, PhD (Summer 2027)

**Company**: Lyft
**Location**: San Francisco, CA
**Job type**: internship
**Category**: Data Science
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/lyft/jobs/8843341002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_4d5fef96-4ea

## Description

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.

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.

## Responsibilities:

- 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

## Experience:

- 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

## Benefits:

- Great medical, dental, and vision insurance options

- Mental health benefits

- In addition to holidays, interns receive 2 days paid time off and 3 days sick time off

- 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

### Required
- Python
- large language models
- agent-based systems
- machine learning
- empirical model evaluation
- A/B testing
- causal inference
- experimental design

### Nice to have
- production level ML inference
- simulation
- evaluation pipelines
- LLM agents
- generative user simulation
- agent-based modeling
- computational social science
- behavioral modeling
- prompting
- tool use
- memory
- planning
- coordination in LLM-based agents

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/lyft/jobs/8843341002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)