
10x offers AI-powered humanoid robots for real-world applications. The system combines AI, robotics, and perception to perform complex tasks in physical environments. It is a robotics platform aimed…

10x offers AI-powered humanoid robots for real-world applications. The system combines AI, robotics, and perception to perform complex tasks in physical environments. It is a robotics platform aimed…
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Origin (previously 10xConstruction) is building general-purpose autonomous robots for US construction to tackle rising costs, safety risks, and labour shortages. Our modular, multi-trade platform combines purpose-built hardware with real-time site intelligence to navigate complex environments and execute tasks with precision. Trained in high-fidelity simulation and already deployed on live sites, our robots deliver 5x faster execution, 250%+ margin expansion, and significant cost savings. Join India’s most talent-dense robotics team consisting of individuals from IITs, Stanford, UCLA, etc.
The Apprentice role at Origin is for high-potential early-career engineers who are ready to contribute immediately. This is not a passive learning role; you will be writing production code from Day 1. You will be assigned specific modules (e.g., a specific sensor driver, a safety monitor, or a diagnostic tool) and expected to deliver robust solutions under the guidance of Senior Engineers.
Module Development:
Develop C++ drivers for auxiliary sensors and actuators within the ROS 2 framework.
Implement state machines for robot subsystems (e.g., gripper logic, battery management).
Optimize existing code for performance and readability.
System Support:
Assist in porting algorithms from Python prototypes to efficient C++ implementations.
Maintain the build system (CMake) and CI/CD pipelines for specific packages.
Perform hardware-in-the-loop (HIL) testing and validate software releases on physical robots.
Debugging & Diagnosis:
Monitor robot telemetry during field tests and flag anomalies in sensor data.
Debug network issues and configuration mismatches in the robot's internal network.