Machine Learning Engineer (Tech Lead — Rider Personalization & Ranking)
End-to-end technical lead for global rider personalization and ranking pipelines serving millions of daily riders across 500+ cities.
- Architected multi-task Mixture-of-Experts (MoE) ranking, calibration, and cross-vertical user representation foundation models trained on distributed NVIDIA A100/B200 GPU clusters.
- Built 0→1 internal agentic developer tooling—including a Ranking Explainer Agent with automated reward-signal graders and an Experiment Config Automator—accelerating ML experimentation velocity.