Senior Product Manager, Rider ML/AI

Lyft•San Francisco, CA

2d•Hybrid

About The Position

Lyft’s Rider Recommendations team is an Applied AI and Machine Learning team that personalizes real-time decisions throughout the Rider App, including search, ride modes, content selection and ranking, and message generation. The team acts as an orchestration layer that determines what riders see. The Senior Product Manager will work closely with machine learning and AI engineers and data scientists, as well as stakeholder teams across Lyft, to define model objectives that align Rider App needs with company goals. The role requires balancing short- and long-term outcomes and partner-team objectives while translating them into unified objectives for the applications. This position owns the roadmap for applied ML and AI products throughout the Rider App and conversion funnel, and is directly accountable for the team’s metrics, KPIs, and financial outcomes. It also involves shaping the rider profile vision, supporting launches, planning and evaluating experiments, writing product documentation, and communicating team progress to technical and nontechnical audiences. The position is hybrid, with three required in-office days per week on Mondays, Wednesdays, and Thursdays, and flexibility to work from anywhere for up to four weeks per year.

Requirements

Experience driving technically complex machine learning products end to end, from inception through launch and significant user adoption to sunset.
Experience managing a team of software engineers from a product perspective and tracking roadmap progress using appropriate tools.
Experience with user-facing, large-scale experimentation and knowledge of concepts such as statistical power and significance.
Experience using AI agents to accelerate day-to-day execution, including understanding code, querying company data, and preparing leadership dashboards.
Knowledge of how machine learning and AI work, including widely used machine-learning and deep-learning packages.
Familiarity with crafting and leading presentations for small groups at the CXO executive level and large teams of 100 or more at all-hands events.
Ability to review and provide critical product feedback on technical specifications written by engineers.
Ability to drive results and operate independently with little supervision in a flat-structured organization.

Nice To Haves

Experience with consumer-facing ML applications involving user interface interactions.
Experience with tools such as Jira, Linear, Spreadsheets, or ClickUp for tracking engineering progress.
Experience with experimentation tools such as Optimizely, Statsig, or Eppo.
Familiarity with packages such as XGBoost, CatBoost, LightGBM, scikit-learn, Keras, and PyTorch, and with the autoresearch approach.

Responsibilities

Define, own, and be responsible for the roadmap of applied ML and AI products across every screen of the Rider Application and through the Rider conversion funnel.
Define, track, and periodically report team metrics and KPIs, with direct responsibility for the team’s financial outcomes.
Define the objective function to be maximized or minimized throughout the rider app, taking into account short-term, long-term, and stakeholder-team objectives.
Work with data science to define, measure, and predict the long-term value of Riders.
Identify how to cold start launches of new regions, modes, and features to drive adoption while maintaining algorithm performance.
Work cross-functionally to build a unified Rider profile vision by identifying, collecting, and organizing information about Riders for ML and AI training.
Write detailed product requirements, strategy, and planning documents for technical and nontechnical audiences to align on product development, delivery milestones, and predictable workstream outcomes.
Design, run, and analyze experiments and ongoing evaluation systems to monitor model performance and evaluate improvements.
Present monthly team progress and roadblocks to nontechnical leadership.

Benefits

Medical, dental, and vision insurance options, with additional programs available upon enrollment.
Mental health benefits.
Family-building benefits.
Child care and pet benefits.
401(k) plan with company match.
12 observed holidays.
Discretionary paid time off for salaried team members; 15 days of paid time off for hourly team members.
18 weeks of paid parental leave for biological, adoptive, and foster parents.
Subsidized commuter benefits.
Monthly Lyft credits and complimentary Lyft Pink membership.
Potential equity offering and bonus.