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Senior Machine Learning Engineer - Semantics - AV Labs

Sunnyvale, CA

Pay
USD 202,000–224,000/year · Base — pay source
~~ ~~ For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 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.
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Work setting
Working pattern needs review — work setting source
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. (https://jobs.uber.com/en/benefits/) Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements. 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. (https://forms.gle/aDWTk9k6xtMU25Y5A?uclick\_id=d56eb634-bfb9-455e-a50d-901b3de0490c)
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Employment
Not stated
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What you’ll work on

Full posting
  • Lead development of autonomy algorithms and foundation models for semantic scene understanding

  • Architect scalable ML systems, including upstream sensor dependencies

  • Deliver high-quality datasets through sensor data collection, processing and auto-labeling

  • Deploy ML techniques into production with platform, product and security teams

From the employer’s posting
Lead the development of autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases
Architect scalable ML systems, including management of upstream sensor dependencies.
Deliver high-quality datasets to accelerate ML technologies through advanced sensor data collection, processing, and auto-labeling.
Partner with platform, product, and security engineering teams to enable the successful deployment of the latest machine learning techniques into production.
Education & alternatives
+ 4+ years of working experience in the ML/Robotics industry. + Bachelor’s degree in Computer Science, Computer Engineering, or related fields. + Proficient in Python and Linux environments.
+ 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.

Tools in this posting

  • C++
  • Python
  • PyTorch
Source — Tool mentions in context
+ Master’s or PhD degree in Computer Vision, Robotics, or Machine Learning. + Familiarity with C++ and high-performance computing. ~~ ~~
+ Bachelor’s degree in Computer Science, Computer Engineering, or related fields. + Proficient in Python and Linux environments. + Familiar with modern AI/ML frameworks (e.g., PyTorch).
+ Proficient in Python and Linux environments. + Familiar with modern AI/ML frameworks (e.g., PyTorch). **Preferred Qualifications**

Posting record

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 29, 2026 · 1 day ago
Recorded sightings
2
Employer says posted
Oct 27, 2026

We found this posting on the National Labor Exchange. These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

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Job description

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**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 Senior 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 the Candidate Will Do** + **Algorithm Development:** Lead the development of autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake. + **Systems Architecture Design:** Architect scalable ML systems, including management of upstream sensor dependencies. + **Technical Leadership:** Partner with fellow engineers to architect, design, and build scalable solutions for ML technology that can stand the test of scale and availability. + **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** + 4+ years of working experience in the ML/Robotics industry. + Bachelor’s degree 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 $202,000 per year - USD $224,000 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. **Ready to Ride?** This isn't the kind of place where you follow a playbook — it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves — we'd love to hear from you. You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. (https://jobs.uber.com/en/benefits/) Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements. 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. (https://forms.gle/aDWTk9k6xtMU25Y5A?uclick\_id=d56eb634-bfb9-455e-a50d-901b3de0490c) Uber is proud to be an Equal Opportunity/Affirmative Action 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- https://docs.google.com/forms/d/e/1FAIpQLSdb_Y9Bv8-lWDMbpidF2GKXsxzNh11wUUVS7fM1znOfEJsVeA/viewform
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Pay
~~ ~~ For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 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.
Location & working pattern

Sunnyvale, CA

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits. (https://jobs.uber.com/en/benefits/) Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements. 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. (https://forms.gle/aDWTk9k6xtMU25Y5A?uclick\_id=d56eb634-bfb9-455e-a50d-901b3de0490c)
Work authorization

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