Currently tracking 13 active AI roles, down 29% versus the prior 4 weeks. Primary focus: Ship · Engineering. Salary range $128k–$222k (avg $171k).
Lyft currently has 28 active AI-related job listings. The majority of these roles, 61%, are focused on agents, with application roles making up another 29%. Engineering is the dominant function, with 21 listings, followed by product with 7. The company is hiring for roles that frequently mention agent orchestration, recommender systems, and model serving. In the last 30 days, Lyft posted 4 new AI roles, a decrease of 73% compared to the previous 30-day period.
Lyft currently has 27 active AI-related roles in our index. The most common open titles are: Data Scientist, Algorithms, Optimization - Fulfillment (3), Applied Scientist- Pricing, Dynamic Pricing & Offer Selection (2), Data Science Manager, Machine Learning - Lyft Ads (2), Senior AI Software Engineer, Risk - Insurance Claims Management (2), Senior Data Scientist - Optimization, Central Market Management & AI (2). Most positions are in Engineering and Product.
Lyft's active AI hiring is concentrated in: agents (59%), application (30%), serving infrastructure (11%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Lyft is hiring AI talent in: United States (19 roles), Canada (8 roles).
Job postings at Lyft most frequently reference: recommender systems, agent orchestration, model serving, evals, search ranking.
In the past 30 days, Lyft has posted 0 new AI-related roles. That is a -100% change versus the prior 30 days (12 → 0).
| Title | Stage | AI score |
|---|---|---|
| Data Science Manager, Rider App Lyft is seeking a Data Science Manager to lead a team focused on improving the Rider App experience through algorithm development, machine learning, and experimentation. The role involves shaping vision, driving execution, and partnering with cross-functional teams to enhance rider relationships and expand to new segments. The ideal candidate will have expertise in advanced analytics, ML, causal inference, experimentation, and a proven track record of leading data science teams in fast-paced environments. | Ship | 7 |
| Machine Learning Engineer, Recommendations Machine Learning Engineer at Lyft focused on developing and launching recommendation algorithms for consumer products. The role involves data analysis, building ML models, writing production code, and evaluating ML systems against business goals. Experience with Python/Golang, supervised learning, forecasting, recommendation systems, reinforcement learning, and multi-armed bandits is required. | Ship |
| 7 |