Lyft is seeking an experienced ML Engineer to drive the development and scaling of their core systems for adaptive experimentation, AI, and pre-experimental measurement to improve decision-making across the company.
Requirements
- 4+ years of hands-on industry experience in machine learning engineering, data science, or causal inference.
- Demonstrated experience in building, deploying, and scaling ML models and pipelines in a production environment.
- Experience with multi-arm bandit (MAB) and LLM frameworks is highly preferred.
Responsibilities
- building and productionizing advanced machine learning systems
- apply machine learning for business and user impact
- Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing problems
- Develop statistical, machine learning, or causal models
- Write production quality code to launch machine learning models at scale
- Evaluate machine learning systems against business goal
Other
- Advanced degree in a quantitative field like computer science, statistics, economics, or engineering, or relevant work experience.
- work 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.
- hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.
