ML Engineer II — Autonomous Driving Data & Systems

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

Benefits offered by this job

Bonus program

Equity award

401(k) plan

Job summary

Uber is building out its AV Labs and seeks a Machine Learning Engineer to develop advanced autonomy algorithms and data-centric ML systems using Physical AI. You will help scale data pipelines, support robust model development, and collaborate across teams to productionize ML methods for real-world driving data.

Ideal candidates have 2+ years in ML/Robotics, a CS degree, Python and Linux proficiency, and PyTorch experience.

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).

Responsibilities

• 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.

Job description

Uber is building out its AV Labs and seeks a Machine Learning Engineer to develop advanced autonomy algorithms and data-centric ML systems using Physical AI. You will help scale data pipelines, support robust model development, and collaborate across teams to productionize ML methods for real-world driving data.

Ideal candidates have 2+ years in ML/Robotics, a CS degree, Python and Linux proficiency, and PyTorch experience.