ML Engineer II: Semantics for Autonomous Driving - Equity

Uber; Sunnyvale (CA); On-site; USD 171,000 - 190,000; Full time

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Benefits

Job summary

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. The ML Engineer role focuses on Physical AI, building advanced autonomy algorithms to add semantic understanding to our driving data and tackle real-world edge cases.

You will develop scalable ML systems, optimize datasets through sensor data collection and auto-labeling, and collaborate with platform, product, and security teams to deploy models into production.

Qualifications

• 2+ 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 such as PyTorch.

Responsibilities

• Develop algorithms and models to extract high-fidelity semantic meaning from urban edge cases.
• Implement scalable ML systems and manage upstream sensor dependencies.
• Deliver high-quality datasets through advanced sensor data collection, processing, and auto-labeling.
• Collaborate with platform, product, and security engineering teams to deploy ML techniques into production.

Skills

Python

Linux

PyTorch

ML systems

Education

Bachelor’s degree in CS/CE or related

Master’s or PhD in CV/Robotics/ML

Tools

C++

GCC

CUDA

Job description

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. The ML Engineer role focuses on Physical AI, building advanced autonomy algorithms to add semantic understanding to our driving data and tackle real-world edge cases.

You will develop scalable ML systems, optimize datasets through sensor data collection and auto-labeling, and collaborate with platform, product, and security teams to deploy models into production.