Field AI is transforming how robots interact with the real world by building risk-aware, reliable, and field-ready AI systems. The Hardware Team at Field AI develops perception and compute payloads that power autonomous robotics systems in complex real-world environments.
Requirements
- B.S., M.S., or Ph.D. in Mechanical Engineering, Electrical Engineering, Robotics, Computer Engineering or related field.
- Several years of experience (5+ years) working with field robotics platforms (UGVs, wheeled/off-road vehicles, quadrupeds, etc.).
- Proven experience leading hardware programs and engineers through to field deployment.
- Embedded compute experience: NVIDIA Jetson, Intel NUC/ARM SBCs, Linux, ROS/ROS2, sensor driver integration, coding (C++, python).
- Sensor integration: LiDAR, depth/stereo cameras, IMU/GNSS, supporting buses (USB, Ethernet, CAN, GMSL, SPI/I2C).
- Sensor synchronization: Strong familiarity with multi-sensor time synchronization (PTP/NTP/PPS), spatial calibration (TF trees, URDF), and autonomy impact.
- Electrical systems: power architecture, onboard vehicle power, harness design, safety interlocks, fault diagnostics, CAN/Ethernet.
- Mechanical/packaging: mounting sensors/compute on mobile platforms, vibration/thermal/ingress isolation, ruggedization for outdoor/field use, CAD design, thermal / structural analysis.
- Systems-level design thinking: ability to trade between compute/thermal/power/sensor/performance constraints.
- Field deployment experience: real-world testing in harsh environments (vibration, dust, extreme temperatures, EMI), root-cause analysis, QA and production readiness.
- Strong cross-discipline collaboration and communication skills. Ability to work with teams across autonomy software, hardware, and field operations.
Benefits
- Generous Paid Time Off
- 401k Matching
- Retirement Plan
- Relocation Assistance