About Origin 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.
About the role As a Perception Engineering Intern / Apprentice at Origin (Formerly 10xConstruction), you will help our autonomous drywall-finishing robots "see" the job-site. You'll design and deploy perception pipelines—camera + LiDAR fusion, deep-learning vision models, and point-cloud geometry—to give the robot the awareness it needs.
Key Responsibilities • Build ROS 2 nodes for 3-D point-cloud ingestion, filtering, voxelisation and wall-plane extraction (PCL / Open3D).
• Train and integrate CNN / Transformer models for surface-defect detection and semantic segmentation.
• Implement RANSAC-based pose, plane and key-point estimation; refine with ICP or Kalman/EKF loops.
• Fuse LiDAR, depth camera, IMU and wheel odometry data for robust SLAM and obstacle avoidance.
• Optimize and benchmark models on Jetson-class edge devices with TensorRT / ONNX Runtime.
• Collect, label and augment real & synthetic datasets; automate experiment tracking (Weights & Biases, MLflow).
Collaborate with manipulation, navigation and cloud teams to ship end-to-end, production-ready perception stacks.
• Solid grasp of linear algebra, probability and geometry; coursework or projects in CV or robotics perception.
• Proficient in Python 3.x and C++17/20; comfortable with git and CI workflows.
Experience with ROS 2 (rclcpp / rclpy) and custom message / launch setups.
• Familiarity with deep-l