Embedded Systems Engineer, Humanoid Robotics

1. Backpack Compute Platform

• Compute Platform Design: Design and select the embedded compute platforms (ARM, SoC, microcontrollers) that power the humanoid payload, balancing capabilities against SWaP constraints.

• Firmware & BSP Bring-Up: Write and customize bare-metal and RTOS firmware, board support packages (BSPs), and bootloaders for the humanoid payloads computing hardware.

• Kernel-Level Development: Work at the Linux kernel level to support real-time performance and reliable operation of the backpack's compute stack.

• Testing & Diagnostics: Conduct thermal profiling, power draw analysis, and latency measurement, and implement watchdogs and health checks for the compute stack.
  
  

2. Sensor & Actuator Drivers

• Perception & State Sensor Drivers: Adapt, integrate, and where needed develop drivers for cameras, LiDAR, and IMUs that feed the backpack's compute platform with real-time perception and state-estimation data.

• Motor, Joint & Tactile Drivers: Adapt, integrate, and where needed develop drivers for motors, joint actuators, and tactile sensors, supporting low-latency control and feedback for humanoid manipulation and locomotion.

• Communication & Timing: Bring up wired (Ethernet, CAN, GMSL, SPI, I2C) and wireless interfaces with deterministic timing (PTP, PPS) across the payload.

3. Manipulation & ML Integration

• ML Team Partnership: Partner closely with the ML team building the robot's software brain to ensure the compute platform meets their latency, memory, and throughput needs.

• Manipulation Data Pipeline: Build the data pipeline connecting camera, LiDAR, IMU, and tactile input to joint manipulation commands, from raw sensor capture through to actuator control.

• Edge ML Enablement: Support accelerated inference on the backpack so ML models can interpret sensor data and issue robot commands in real time.
  ROS/DDS Middleware: Expose driver and sensor data through ROS/ROS2 and DDS interfaces so the ML team's software brain can consume it in real time.
  
  

4. Cross-Platform Generalization & Collaboration

• Platform Abstraction: Design the backpack's compute and software architecture to generalize across a diversity of humanoid robot platforms.

• Cross-Team Collaboration: Work closely with mechanical, electrical, and sensor engineers to develop a tightly integrated backpack payload.

• Technical Leadership: Lead the technical direction of backpack compute development, from architecture decisions through implementation.

• Safety & E-Stops: Implement e-stop circuitry and safety monitoring on the backpack platform, laying the groundwork for functional safety as the fleet matures.
  

• Education: B.S., M.S., or Ph.D. in Computer Engineering, Electrical Engineering, Robotics, or a related field.

• Experience Level: Minimum of 3+ years of hands-on experience with embedded systems.. We welcome candidates across mid-level to senior and staff levels.

• Programming: Proficient in C++ and Python for embedded and application-level development.

• Embedded Systems Experience: Experience bringing up and customizing bare-metal and RTOS firmware, Linux kernel and device drivers, and board support packages (BSPs), across platforms such as Jetson or custom SBCs.

• Driver Development: Experience developing drivers for cameras, LiDAR, IMUs, tactile sensors, or motors, connecting sensors and actuators to embedded compute.

• ML/Edge Acceleration: Familiarity with GPU, TPU, or NPU offload and frameworks such as CUDA or TensorRT for edge inference, ideally supporting manipulation or perception models.

• Real-Time Communication Protocols: Hands-on experience with Ethernet, CAN/CAN-FD, SPI, I2C, UART, USB, or PCIe, wireless links, and timing protocols such as PTP.

• ROS & Middleware: Familiarity with ROS/ROS2 and DDS for exposing sensor and actuator interfaces to higher-level software.

• SWaP-Constrained Design: Experience designing compute hardware and firmware under tight size, weight, and power (SWaP) constraints, such as wearable or backpack-style payloads.

• Humanoid Robotics Experience: Experience developing embedded systems, firmware, or drivers for humanoid or other legged robot platforms.

• Manipulation & Robot Control Knowledge: Familiarity with joint manipulation, motor control, and how sensor data flows into robot commands such as standing or grasping.

• Kernel-Level Development: Experience with Linux kernel modules, device driver development, kernel-level debugging, PREEMPT_RT, and deterministic, low-jitter timing in production systems.

• Safety-Critical Systems: Experience implementing e-stop circuitry, safety monitoring, or other safety-critical embedded systems for robots operating near people. Experience with functional safety standards such as ISO 13849 or ISO 10218 for robots operating in human environments.

• ML Collaboration: Experience working directly with ML or perception teams to meet model latency, memory, and throughput requirements on embedded hardware.