At Lyft, the business problem is to cultivate a work environment where all team members belong and have the opportunity to thrive, and to architect the intelligent layer of the Rider experience through applying state-of-the-art AI techniques to deliver hyper-personalized experiences for every rider, every ride.
Requirements
- Strong proficiency in Python, ML frameworks and distributed data systems
- Experienced in defining and executing offline and online evaluation strategies, including experiment design, counterfactual analysis, and diagnostics for system failures.
- Master’s or PhD in Machine Learning, Computer Science, Optimization, Statistics, Engineering, Applied Mathematics, or a related quantitative field; or equivalent high-impact industry experience.
- 5+ years of applied science or machine learning experience, with a track record of deploying production models that drive measurable business outcomes.
- Experienced in owning multi-project modeling scope across ambiguous problem spaces and integrating work across engineering, product, and data science partners.
- Strong technical leadership skills — able to align partners, influence technical architecture, challenge assumptions, and guide cross-team modeling decisions.
- Experience in mentoring other scientists, elevating technical quality, and improving modeling/analysis standards across the team.
Responsibilities
- Own complex, open-ended problem spaces. Translate vague business problems into concrete mathematical objectives.
- Lead multiple high-impact Machine Learning and AI initiatives that powers rider core product experience. Drive algorithmic innovation by introducing new techniques.
- Design, develop, and deploy advanced machine learning, optimization, and decisioning algorithms for large-scale real-time inferences, balancing scientific rigor with practical engineering constraints.
- Establish robust evaluation frameworks, defining offline metrics, calibration checks, counterfactual methods, experiment designs, and long-term measurement strategies to ensure model correctness and system stability.
- Build reusable modeling infrastructure, libraries, and best practices, enabling faster iteration and higher modeling quality across the broader Rider Science and Engineering teams.
- Mentor and guide junior/mid-level scientists, serving as a technical advisor on modeling design, experimentation, code quality, and scientific reasoning.
- Partner deeply with Product, Design and Engineering to define technical vision for how AI will transform Lyft rider experience.
Other
- Master’s or PhD in a related quantitative field; or equivalent high-impact industry experience.
- 5+ years of applied science or machine learning experience
- Excellent communication skills, with the ability to articulate complex modeling concepts, system trade-offs, and scientific reasoning to both technical and business stakeholders.
- Strong technical leadership skills — able to align partners, influence technical architecture, challenge assumptions, and guide cross-team modeling decisions.
- Experience in mentoring other scientists, elevating technical quality, and improving modeling/analysis standards across the team.
