Embedded Systems Engineer, Humanoid Robotics

FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use. Hardware Team: The Hardware Team at FieldAI develops perception and compute payloads that power autonomous robotics systems in complex real world environments. Our work spans the full hardware stack designing and integrating sensing systems (LiDAR, camera, TOF, IMU, GPS), embedded compute (CPUs, GPUs, microcontrollers, Linux, ROS), electrical systems (power distribution, communication), and mechanical components (structures, thermal regulation, ingress protection). The team focuses on both development (research, design, prototyping, testing) and operations (production, testing, QA, debugging). We’re a small, fast-moving team, and we care deeply about improving: 1) core capabilities, 2) system reliability, 3) system scalability. As a growing team we are also building operational systems and procedures from the ground up.   Embedded Systems Engineer: In this role you will develop computing systems for humanoid robots. This may span compute platform design (ARM, SoC, microcontrollers), firmware and BSP bring-up, and kernel-level Linux work. Work will focus on a robot payload that intakes LiDAR, camera, IMU, and tactile sensor information and then outputs joint manipulation and locomotion commands that let the robot stand, move, and use its hands.  You will partner closely with the ML team building the robot's software brain, ensuring the compute platform can run their perception and manipulation models with the latency and throughput they need. The system is designed to operate across a diversity of humanoid robot platforms, so your work will generalize across different hardware rather than target a single robot. You will collaborate closely with the mechanical, electrical, and ML teams to build tightly integrated, safety-conscious solutions ready for deployment in the field.