Embedded Systems Engineer for Humanoid Robotics | Real-Time

Field Ai; Boston (MA); On-site; USD 120,000 - 160,000; Full time

Job summary

Field AI is seeking an Embedded Systems Engineer to build compute platforms for humanoid robots, including ARM/SoC platforms, firmware bring-up, and kernel work. You will work with LiDAR, cameras, IMUs, and tactile sensors to feed a real-time control loop for standing, moving, and manipulating objects.

You will collaborate with ML, mechanical, electrical, and software teams to deliver safe, scalable backpack compute solutions and ensure deterministic performance for edge inference and perception

Qualifications

• Education: B.S., M.S., or Ph.D. in Computer Engineering, Electrical Engineering, Robotics, or related field.
• 3+ years hands-on embedded systems experience.
• Proficient in C++ and Python for embedded and application-level development.
• Experience bringing up bare-metal and RTOS firmware, Linux kernel and drivers.
• Driver development for cameras, LiDAR, IMUs, tactile sensors or motors.
• Familiarity with GPU/TPU/NPU offload and edge frameworks (CUDA/TensorRT).
• Hands-on with Ethernet, CAN, SPI, I2C, UART, USB, PCIe and timing protocols.
• Familiarity with ROS/ROS2 and DDS for data exposure.

Responsibilities

• Design backpack compute platforms and select embedded hardware under SWaP constraints.
• Develop firmware, BSP bring-up, and kernel-level Linux support for real-time operation.
• Develop and integrate drivers for perception sensors and actuators.
• Collaborate with ML team and expose data via ROS/ROS2 and DDS.

Skills

C++

Python

Embedded systems

Linux kernel

Drivers development

ROS/ROS2

SWaP constraints

Real-time tech

Education

B.S., M.S., or Ph.D. in Computer Engineering, Electrical Engineering, Robotics, or related field

Job description

Field AI is seeking an Embedded Systems Engineer to build compute platforms for humanoid robots, including ARM/SoC platforms, firmware bring-up, and kernel work. You will work with LiDAR, cameras, IMUs, and tactile sensors to feed a real-time control loop for standing, moving, and manipulating objects.

You will collaborate with ML, mechanical, electrical, and software teams to deliver safe, scalable backpack compute solutions and ensure deterministic performance for edge inference and perception