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Lyft Articles

Lyft

31 min read

Machine Learning•2026-03-30

Predicting Rider Conversion in Sparse Data Environments with Bayesian Trees

This post describes how Lyft built a Bayesian hierarchical tree model to predict rider conversion in real-time under sparse data conditions.

Data Engineering•2026-03-25

Beyond A/B Testing: Using Surrogacy and Region-Splits to Measure Long-Term Effects in Marketplaces

This article presents Lyft's two-step methodology for estimating long-term market-mediated effects of marketplace policy changes using a surrogacy and region-split approach.

Lyft

01 min read

AI•2026-02-19

Scaling Localization with AI at Lyft

Lyft rebuilt its translation pipeline by integrating LLMs to reduce translation latency from days to minutes while maintaining linguist oversight.

artificial-intelligence

Machine Learning•2026-02-12

Trusting the Untestable: Validation and Diagnostics for the Doubly Robust Models

This post from Lyft explains how they validate and diagnose Doubly Robust (AIPW) models used for causal inference when A/B testing is not feasible.

Data Engineering•2026-01-06

Lyft’s Feature Store: Architecture, Optimization, and Evolution

This article describes the architecture, optimization, and evolution of Lyft's Feature Store, a core ML infrastructure platform serving 60+ use cases across the rideshare stack.

From Python3.8 to Python3.10: Our Journey Through a Memory Leak

This post details Lyft's investigation into a memory leak and latency regression discovered while upgrading a Python service from 3.8 to 3.10.

Machine Learning•2025-11-18

LyftLearn Evolution: Rethinking ML Platform Architecture

This post describes how Lyft evolved LyftLearn, their end-to-end ML platform, from a fully Kubernetes-based system to a hybrid architecture combining AWS SageMaker and Kubernetes.

distributed-systems

artificial-intelligence

Machine Learning•2025-10-07

My Starter Project on the Lyft Rider Data Science Team

This post describes a Lyft data scientist's starter project using the Rider Experience Score (RES) tool to estimate long-term causal effects of rider experiences on retention without relying on A/B tests.

artifical-intellegence

Lyft

01 min read

Mobile•2025-09-09