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Based on 240 similar postings.
Employer
About Uber
Uber Technologies, Inc. is the world’s largest, San Francisco-based mobile technology platform facilitating on-demand ride-hailing, food delivery (Uber Eats), and freight transportation across approximately 70 countries.
Staff System Engineer - AV Labs joins the AV Labs team to accelerate the autonomous technology ecosystem by turning real-world operations into high-quality data. In this role, you will lead technical assessments, capability benchmarking, and system integration validation for autonomous systems. You will develop multi-modal metrics to benchmark performance against human capabilities, build safety cases, and perform hazard analyses to ensure fault management logic aligns with internal standards. You will act as a technical liaison between internal and external engineering organizations to manage release gating criteria. The position requires proficiency in Python and Linux environments, along with experience in robotics or autonomous systems. You will solve the challenge of unlocking long-tail driving data and establishing rigorous performance evaluations for the safe, scalable deployment of autonomous vehicles.
Lead technical assessments and capability benchmarking for partner autonomous systems.
Audit partner performance against safety and efficiency KPIs to validate technology readiness.
Define and execute integration strategies for hardware and software components.
Develop multi-modal metrics to benchmark system performance against human capabilities.
Build safety cases and hazard analyses to ensure alignment with internal safety standards.
Act as the primary technical point of contact between internal and external engineering organizations.
Manage technical gating criteria for releases and track issues to resolution.
What we're looking for
6+ years of working experience in the Robotics or Autonomous Systems industry.
Bachelor’s or Master’s degree in Computer Science, Transportation Engineering, Statistics, Computer Engineering, Electrical Engineering, or related fields.
Proficiency in Python and Linux environments.
Strong system thinking skills to decompose complex driving capability challenges into scalable solutions.
Professional experience in safety critical autonomous systems or PhD research experience in traffic safety (preferred).
Proven track record of defining release processes and safety criteria for real-world autonomous systems (preferred).
Hands-on experience with system validation tools with development skills on simulation and data mining (preferred).
Background in functional safety, SOTIF, or Cybersecurity for automotive development (preferred).
Python
PyTorch
C++
CUDA
Linux
ROS
Machine Learning
Computer Vision
Foundation Models
Robotics
Autonomous Systems
System Design
Data Mining
Auto-labeling Systems
Systems Engineering
Embedded Systems
ADAS
AV
RTOS
Embedded Linux
System Architecture
Requirements Management
Simulation Tools
Telemetry
Profiling
Ethernet
GPU
NPU
CPU
Robotics