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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.
The Fleet Engineering Lead joins the AV Labs team to accelerate the autonomous technology ecosystem by turning real-world operations into high-quality data. This role serves as the on-site technical lead at the intersection of Hardware Engineering, Software Engineering, and daily fleet operations. Key responsibilities include bootstrapping data collection in new cities, performing advanced diagnostics on complex hardware and software faults, and validating upfitted vehicles. You will design triage and calibration playbooks, conduct technical audits, and develop scripts to automate repetitive tasks. Required skills include Linux troubleshooting, Python or Bash scripting, and experience with networking, LiDAR, Radar, Cameras, IMU, and automotive data links like CAN or Automotive Ethernet. The role solves the bottleneck of unlocking long-tail driving data for autonomous vehicle partners.
Launch data collection in new cities by overseeing technical setup from vehicle hardware to data offload.
Serve as the final on-site escalation point for complex, undocumented hardware and software faults.
Perform deep root-cause analysis on system issues that exceed standard troubleshooting guides.
Validate hardware and software integration on newly upfitted vehicles and evaluate depot-level serviceability.
Design, test, and document core triage, calibration, and maintenance playbooks for fleet standardization.
Conduct cross-site technical audits to ensure uniform execution and resolve local operational bottlenecks.
Develop local scripts and tooling to automate repetitive tasks like firmware deployment.
Train local contractor staff on technical playbooks and operational cadences.
What we're looking for
5+ years of experience in an advanced technical role with complex electromechanical systems, autonomous vehicles, aerospace testing, or enterprise hardware integration.
Strong problem-solving ability to navigate ambiguous and fast-changing environments.
Proficiency in Linux troubleshooting and scripting using Python or Bash (preferred).
Proven track record of documenting complex technical workflows, writing SOPs, and training technical teams.
Deep familiarity with networking, sensor integration (LiDAR, Radar, Cameras, IMU), or automotive data links (CAN, Automotive Ethernet, GMSL).
Willingness to travel up to 50% of the time.
Direct experience with L4 autonomous vehicle hardware platforms, sensor calibration rigs, and data collection workflows (preferred).
Experience as a bootstrap lead, NPI technician, or landing team member for new operational sites (preferred).
Python
PyTorch
C++
Linux
Machine Learning
Computer Vision
Robotics
High-Performance Computing
System Design
Algorithm Development
Data Mining
Auto-labeling
Physical AI
Causal Modeling