End-to-End Embodied AI Engineer for Robotics

XDOF; San Mateo (CA); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Competitive compensation

Flat engineering culture

Hardware lab resources

Flexible work arrangements

Learning programs

Job summary

XDOF in California is seeking a full-stack engineer to own end-to-end embodied AI deployment on robots, spanning hardware, sensors, data pipelines, and algorithm deployment.

You will work across the stack with ROS2, camera systems, and robotic arms, delivering robust data collection and model inference workflows. Strong Python/C++ skills and PyTorch experience are essential; UX/hard realtime challenges are common.

Qualifications

• Bachelor's degree in Robotics, Automation, CS, or related field with 3+ years of experience.
• Strong Python and C++ programming skills; Linux system-level development.
• Expertise in ROS/ROS2 and node communication, topics, services, actions, and Launch.
• Hands-on with camera systems (ZED/RealSense) and robotic arms; calibration basics.
• Experience training and deploying deep learning models with PyTorch.

Responsibilities

• Maintain and extend embodied AI data collection systems and pipelines.
• Integrate and calibrate camera systems and robotic arms; keep hardware stable.
• Own end-to-end deployment of imitation learning and teleoperation on robots.
• Ensure data quality: synchronization, frame alignment, anomaly detection, repair.
• Define robot software interfaces and ROS2/DDS communication for replication.
• Support on-site data collection, deployment, and documentation; improve efficiency.

Skills

Python

C++

ROS2

Linux

PyTorch

Camera calibration

Robotics hardware

AI tooling (Claude Code)

Data pipelines

Education

Bachelor's degree in Robotics or CS

Tools

ROS

RealSense/ZED SDK

Jetson

CAN / EtherCAT

Job description

XDOF in California is seeking a full-stack engineer to own end-to-end embodied AI deployment on robots, spanning hardware, sensors, data pipelines, and algorithm deployment.

You will work across the stack with ROS2, camera systems, and robotic arms, delivering robust data collection and model inference workflows. Strong Python/C++ skills and PyTorch experience are essential; UX/hard realtime challenges are common.