Fleet Support Engineer - Sensors

JOB TITLE:
Fleet Support Engineer - Sensors

LOCATION:

Foster City, CA (Onsite)
PAY RANGE: $75 - $85/hr.
DURATION: 6 Months

TOP 3 SKILLS:

• 6+ years of experience in automotive, autonomous vehicles, aerospace, or transportation with a Bachelor s degree in Mechanical, Electrical, or Automotive Engineering
• Strong experience with sensor systems (LiDAR, cameras, radar), including calibration, integration, and field troubleshooting
• Strong background in system-level root cause analysis and vehicle diagnostics using tools like Wireshark, Vector tools, and electrical schematics

Job Description:
The Fleet Support Engineer on the Vehicle Development team serves as the highest level (Tier
3) of field technical support, focused on systemic reliability of fleet vehicles. You will be a subject matter expert in sensor systems, supporting our Tier 2 (Regional) Fleet Support Engineers on their most complex escalations. Through fleet-wide analysis of diagnostics and metrics, you will identify reliability gaps, drive down mean repair and escalation times through improved tooling/documentation, and feed critical design changes back to Hardware Engineering.

Responsibilities:

• Serve as the primary point of contact for Tier 3 escalations on sensor-related fleet issues, including LiDAR, cameras, and radar.
• Diagnose and resolve complex hardware, software, tooling, or process failures related to sensors and perception systems using comprehensive log review and data analysis
• Develop thorough troubleshooting guides for Tier 1 and Tier 2 escalations, enabling consistent and holistic diagnosis across all service depots.
• Lead deep-dive investigations into Client failure modes using root cause analysis methodologies like 7-Step or 8D (8 Disciplines) problem-solving techniques.
• Develop engineering solutions as short-term mitigations and long-term correction actions to improve vehicle safety and reliability, preventing recurring issues.
• Perform hardware bring-up and validation procedures for new vehicle components.
• Monitor fleet-wide telemetry to identify emerging trends in hardware degradation or firmware/software regression before they become critical failures.
• Drive closed-loop feedback by translating field failure data into engineering change requests to improve sub-system design.

Qualifications:

• Minimum 6+ years of relevant experience in automotive, autonomous vehicles, transportation, or aerospace.
• Bachelor s degree in Mechanical Engineering, Electrical Engineering, or Automotive Engineering.
• Deep understanding of LiDAR, cameras, and radar hardware including calibration, integration, and field troubleshooting.
• Familiarity with data formats and pipelines used by perception systems (e.g., point clouds, image streams, radar returns).
• Proficiency with network analysis tools (e.g., Wireshark, Vector tools) for Automotive Ethernet debugging
• Proficiency with interpreting electrical schematics, harness diagrams, and state machine diagrams.
• Ability to perform system-level root cause analysis down to the component level.
• A proactive self-starter who can build strong relationships and communicate efficiently and effectively across various teams and in real-time service operation settings.

Bonus Qualifications:

• Experience with electric vehicle technology.
• Experience with remotely supporting vehicle troubleshooting.
• Experience with Automotive Ethernet (100
  
  BASE-T1, 1000
  
  BASE-T1) for high-bandwidth sensor data transport
• Knowledge of vehicle systems, diagnostic tools, Unified Diagnostic Services (UDS) and Ethernet-based diagnostics (DoIP).
• Experience with Linux & Python for fleet-level data processing.

BENEFITS

SUMMARY:

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate or annual salary only, unless otherwise stated. In addition to base compensation, full-time roles are eligible for Medical, Dental, Vision, Commuter and 401K benefits with company matching.

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