Serve Robotics is looking to solve the problem of developing robust fault detection, diagnosis, and recovery systems for their autonomous robots to enhance reliability, resilience, and operational safety.
Requirements
- Strong proficiency in C++ and Python, with experience in real-time and distributed systems.
- Solid understanding of autonomy architectures, including perception, planning, localization and control pipelines.
- Hands-on experience with ROS/ROS2 or similar robotic middleware.
- Familiarity with fault-tolerant design, FMEA, diagnostics, or reliability engineering.
- Background in autonomous vehicles, mobile robotics, or field robotics.
- Experience with system telemetry, health monitoring, and data-driven validation.
- Knowledge of state machines, behavior trees, or similar frameworks for failure management.
Responsibilities
- Design and implement fault detection and recovery frameworks across autonomy and control components.
- Lead Failure Modes and Effects Analysis (FMEA) activities and translate findings into actionable software mechanisms.
- Develop health monitoring and diagnostics systems to assess real-time component and subsystem performance.
- Implement state management and recovery logic for scenarios like sensor degradation, controller faults, and odometry resets.
- Define and execute degradation-aware behaviors to ensure safe operation under partial system failures.
- Establish end-to-end performance and latency monitoring to support fault-tolerant autonomy.
- Contribute to ODD (Operational Design Domain) detection and management, ensuring appropriate system response to environmental changes.
Other
- 3+ years of experience in robotics or autonomous systems software development.
- Proven ability to collaborate across software and hardware teams to deliver resilient robotic systems.
- Understanding of SOTIF or related safety frameworks.
- Exposure to machine learning or analytics for anomaly and fault detection.
- The base salary range listed in this job description reflects compensation for candidates based in the San Francisco Bay Area. While we prefer candidates located in the Bay Area, we are also open to qualified talent working remotely across the United States.
