Robotics Systems Integration Engineer, Robotics Hardware

Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.

As a Robotics Integration Engineer on the Hardware Team at Field AI, you will bring new robot platforms into our fleet and ensure that they operate at high standards in real world environments. This will involve integrating our control systems, autonomy stack, and payloads onto new robotic platforms. Your work will span across areas including platform abstraction, robot control, autonomy, sim-to-real validation, and electro-mechanical integration. 

Responsibilities may include the full lifecycle from initial platform bring-up through safety qualification and field deployment. You will collaborate closely with the Autonomy/RL, Manipulation, Mechanical, and Electrical teams to build tightly integrated solutions ready for deployment in challenging field environments. Additionally while your focus will be on platform integration, you may contribute across hardware, field operations, and autonomy domains.

• Multi-Platform Experience: Experience integrating software across multiple robot platforms, including legged/quadruped, humanoid, and wheeled UGVs (e.g., Unitree, Boston Dynamics, Clearpath).

• Field Environments: Experience deploying robots in harsh, diverse industrial field environments such as construction, mining, and oil & gas.

• Functional Safety: Background in functional safety standards (ISO 26262, ASIL, SOTIF/ISO 21448) and safety-critical systems testing and validation.

• Advanced Controls: Experience with whole-body control, impedance/admittance control, MPC, or trajectory optimization for legged or manipulator systems.

• Fleet & Infrastructure: Experience with multi-robot fleet operations, auto-docking/charging infrastructure, or teleoperation systems