Sr Software Engineer, MLE - AV Labs

Uber; Sunnyvale (CA); On-site; USD 202,000 - 224,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Job summary

Uber is launching AV Labs in Sunnyvale to accelerate autonomous technology with massive real-world driving data. We seek a Senior ML Engineer to build advanced autonomy models and semantic data, delivering robust and scalable ML systems for production.

Qualifications include 4+ years in ML/Robotics, Python and Linux proficiency, PyTorch familiarity, and C++/HPC comfort. Ideal candidates have autonomous driving experience and advanced degrees.

Qualifications

• 4+ years of experience in ML/Robotics.
• BS in Computer Science, Computer Engineering, or related fields.
• Proficient in Python and Linux environments.
• Familiar with modern AI/ML frameworks (e.g., PyTorch).
• Experience in Autonomous Driving domain.
• Proven track record of deploying ML models in safety-critical physical systems.
• Master's or PhD in Computer Vision, Robotics, or ML.
• Familiarity with C++ and high-performance computing.

Responsibilities

• Lead the development of autonomy algorithms and foundation models to enrich our data lake.
• Architect scalable ML systems with management of upstream sensor dependencies.
• Provide technical leadership to design and build scalable ML solutions for production.
• Deliver high-quality datasets via advanced sensor data collection, processing, and auto-labeling.
• Collaborate with platform, product, and security teams to deploy ML techniques into production.

Skills

Python

Linux

PyTorch

Autonomous Driving

Safety-critical ML

C++

Education

Bachelor's degree in Computer Science or Computer Engineering or related fields

Master's or PhD in Computer Vision, Robotics, or Machine Learning

Job description

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.

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.

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.

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