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Machine Learning Engineer II - AV Labs

Machine Learning, Engineering
in Sunnyvale, California
- Full Time

About the Role

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We're building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data for our autonomous partners. This team is focused on the hardest problem in AV today: unlocking real-world, long-tail driving data. Autonomy is now a data race—and Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match.

As a ML Engineer, you will be at the forefront of Physical AI, building advanced autonomy algorithms and models to add rich semantics to our massive driving data. You will be responsible for the development and implementation of the latest machine learning techniques that enables better data mining, deep scene understanding, and causal modeling of ego vehicle behavior.The ideal candidate will be able to identify complex edge cases, provide robust algorithmic solutions, and set a high technical excellence bar.

What You Will Do

  • Algorithm Development: Develop algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake.
  • System Design: Implement scalable ML systems, including management of upstream sensor dependencies.
  • Dataset Optimization: Deliver high-quality datasets to accelerate ML technologies through advanced sensor data collection, processing, and auto-labeling.
  • Cross-Functional Collaboration: Partner with platform, product, and security engineering teams to enable the successful deployment of the latest machine learning techniques into production.

Basic Qualifications

  • 2+ years of working experience in the ML/Robotics industry.
  • Bachelor’s degree (or higher) in Computer Science, Computer Engineering, or related fields.
  • Proficient in Python and Linux environments.
  • Familiar with modern AI/ML frameworks (e.g., PyTorch).

Preferred Qualifications

  • Experience in the Autonomous Driving domain.
  • Proven track record of deploying ML models in safety-critical physical systems.
  • Master’s or PhD degree in Computer Vision, Robotics, or Machine Learning.
  • Familiarity with C++ and high-performance computing.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.


See our Candidate Privacy Statement

Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, Veteran Status, or any other characteristic protected by law.

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ご希望の言語を選択してください

アラビア語, العربيةアッサム語, অসমীয়াアゼルバイジャン語, Azərbaycancaブルガリア語, Българскиベンガル語, বাংলাカタロニア語 (スペイン), Català (Espanya)チェコ語, Češtinaデンマーク語, Danskドイツ語, Deutschギリシャ語, Ελληνικά英語, Englishスペイン語, Español (Internacional)スペイン語, Español (Argentina)スペイン語, Español (Chile)スペイン語, Español (Colombia)スペイン語, Español (Costa Rica)スペイン語 (イベリア半島), Castellanoスペイン語, Español (Honduras)スペイン語, Español (México)スペイン語, Español (Uruguay)エストニア語, Eestiフィンランド語, Suomiフランス語 (カナダ), Français (Canada)フランス語, Français (France)ヘブライ語, עבריתヒンディー語, हिन्दीクロアチア語, Hrvatskiハンガリー語, Magyarインドネシア語, Bahasa Indonesiaイタリア語, Italiano日本語, 日本語ジョージア語, ქართულიカンナダ語, ಕನ್ನಡ韓国語, 한국어クルド語, کوردیリトアニア語, Lietuviųラトビア語, Latviešuマラヤーラム語, മലയാളംマラーティー語, मराठीノルウェー語(ブークモール), Norsk Bokmålネパール語, नेपालीオランダ語, Nederlandsパンジャブ語, ਪੰਜਾਬੀポーランド語, Polskiポルトガル語 (ブラジル), Português (Brasil)ポルトガル語 (イベリア半島), Português (Portugal)ルーマニア語, Românăロシア語, Русскийシンハラ語 (スリランカ), සිංහලスロバキア語, Slovenčinaスロベニア語 (スロベニア), Slovenščinaスウェーデン語, Svenskaスワヒリ語, Kiswahiliタミル語, தமிழ்テルグ語, తెలుగుタイ語, ไทยトルコ語, Türkçeウクライナ語, Українськаウルドゥー語, اردوベトナム語, Tiếng Việt中国語, 简体中文中国語 (中華人民共和国香港特別行政区), 香港中文中国語 (台湾), 繁體中文