PhD Machine Learning Software Engineer Intern

What you'll do

• Own a research project from framing the problem to designing rigorous offline and online evaluations.
• Design, build, train, and test ML models for reinforcement learning, sequential decision-making, and personalization.
• Write production-quality code to transform research prototypes into working pipelines on Lyft's infrastructure.
• Analyze experimental and observational data to communicate findings to technical and non-technical audiences.
• Write up research results for publication at peer-reviewed venues.
• Participate in code and spec reviews to ensure high code quality and knowledge distribution.

What we're looking for

• Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Operations Research, Applied Mathematics, or a related technical field.
• Must be returning to your program after the internship with a graduation date between December 2027 and Summer 2028.
• A track record of ML research shown through publications, preprints, or substantial research projects.
• Strong foundation in reinforcement learning and sequential decision making, especially problems with delayed or long-horizon rewards.
• Solid grounding in both causal inference and counterfactual evaluation.
• Strong programming skills in Python or a similar language.
• Good understanding of ML libraries like PyTorch, TensorFlow, or JAX.
• Proven ability to effectively turn research ML papers into working code.