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Uber AV Labs

Where autonomy meets reality

Today’s challenges for autonomy aren’t on closed tracks; they’re in the real world. Autonomy is now a data and modeling race—and few companies have more real-world driving data than Uber. With data from billions of trips at our disposal, Uber AV Labs is positioned to turn this complexity into high-quality learning signals that vastly accelerate the advancement of autonomous systems.

Write the next chapter of autonomy

At AV Labs, you’ll work on the learning core of autonomy—building systems across data mining, machine learning, simulation, validation, and infrastructure that transform raw real-world operations into usable training and evaluation pipelines.

“Autonomy is now a game of long-tails. AV Labs will turn these rare critical scenarios into signal sets to close the gap between research and real-world AV performance.”

Ready to accelerate AVs?

Ideal candidates will have experience in the following skill sets: machine learning, applied AI, computer vision and perception systems, data systems, data mining and evaluation, simulation, validation, autonomy tooling, infrastructure, and large-scale distributed systems.

  • Senior Staff Machine Learning Engineer
  • Staff Machine Learning Engineer
  • Senior Machine Learning Engineer
  • Machine Learning Engineer II
  • Group Product Manager
  • Lead Product Manager
  • Senior Product Manager

有興趣嘗試其他職位嗎?

如果你想加入 Uber AV Labs,但目前無法申請這些開放職缺,請填寫連結頁面上的一般意願表單。

Team leadership

Danny Guo

工程與科學部門副總裁

Danny 是一位資深的 Uber 工程領導者,擁有自動化、地圖繪製及市場經濟等領域的深厚專業。他曾打造並擴展多項 Uber 業務關鍵平台,涵蓋即時系統、機器學習與最佳化等交會領域。

Abhinav Gupta

產品管理總監

Abhinav 是一位具有豐富經驗的產品主管,專長於自主技術與具身人工智慧。他曾主導產品願景與策略規劃,從早期的機器人技術研究一路推進到面向消費者的自動駕駛車輛部署,成功將創新技術轉化為具體的社會影響力。

Min Cai

傑出工程師

Min 負責主導等級 4 自動駕駛與 Uber 人工智慧平台的資料蒐集工作。他對自動駕駛的熱情始於早期參與 Uber ATG 的人工智慧基礎建設,涵蓋 GPU 叢集到分散式訓練系統。他加入 Uber 已逾 11 年,也曾領導多項重要的平台工程計畫。

Yimeng Zhang

Sr Director, Autonomous

Yimeng is a technical leader in autonomous systems, with extensive expertise across deep learning, large-scale AI systems, and end-to-end engineering that takes autonomy from research to the real world, delivering safe and scalable solutions across complex operational domains.