Field AI is transforming how robots interact with the real world by building risk-aware, reliable, and field-ready AI systems for autonomous robotics. The company is seeking to address complex challenges in robotics through real-world deployment and improvement of AI models.
Requirements
- 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.
Responsibilities
- Collaboratively direct the architecture and implementation of the UGV sensing and computing hardware to enable autonomy.
- Direct sensor and compute payload integration: LiDAR, depth/stereo cameras, IMU/GNSS, embedded compute platforms (NVIDIA/Intel), time synchronization, ROS/ROS2 middleware.
- Direct electrical design and platform integration: vehicle power distribution, onboard DC/AC systems, CAN/Ethernet networks, wiring harnesses, E-stop/fault handling, diagnostics.
- Direct mechanical integration activities: platform mounting on a wheeled UGV, ruggedization including vibration/thermal/ingress protection, ingress/egress for maintainability.
- Define and execute field-test readiness: develop test plans (thermal, vibration, EMI/EMC, power, latency/data integrity), lead debugging workflows and field root-cause analysis.
- Collaborate with autonomy software: drive hardware/sensor requirements aligned with autonomy algorithms, lead trade-offs across compute, power, sensing and mechanical constraints.
- Manage vendors and procurement: select sensors, compute modules, harnesses, mechanical components; establish QA checks; drive production readiness and scaling.
Other
- 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.). Ideally with experience across sensors, compute, mechanical and electrical systems.
- Proven experience leading hardware programs and engineers through to field deployment.
- U.S. citizenship strongly preferred. Experience with or eligibility for security clearance (Secret, TS/SCI) highly desirable.
- Strong cross-discipline collaboration and communication skills. Ability to work with teams across autonomy software, hardware, and field operations.
