{"id":3007178,"url":"https://alion.io/job/origin-perception-engineer-apprentice-2","title":"Perception Engineer - Apprentice","company":{"id":686527,"name":"Origin","domain":"origin.tech","url":"https://alion.io/company/origin-7","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":100,"open_postings":23,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":35,"computed_at":"2026-10-22T06:10:10Z"}},"role":"Robotics","role_family":"Robotics","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"CNN","optional":false},{"name":"GTSAM","optional":false},{"name":"MLFlow","optional":false},{"name":"Obstacle Avoidance","optional":false},{"name":"ONNX Runtime","optional":false},{"name":"Open3D","optional":false},{"name":"Perception","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"ROS","optional":false},{"name":"SLAM","optional":false},{"name":"TensorFlow","optional":false},{"name":"TensorFlow C++","optional":false},{"name":"TensorRT","optional":false},{"name":"Transformers","optional":false},{"name":"Weights & Biases","optional":false}],"status":"live","first_seen_at":"2026-10-19T00:00:00Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-22T10:55:01Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About Origin\nOrigin (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.\nAbout the role\nAs 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.\nKey Responsibilities\nBuild ROS 2 nodes for 3-D point-cloud ingestion, filtering, voxelisation and wall-plane extraction (PCL / Open3D). \nTrain and integrate CNN / Transformer models for surface-defect detection and semantic segmentation. \nImplement RANSAC-based pose, plane and key-point estimation; refine with ICP or Kalman/EKF loops. \nFuse LiDAR, depth camera, IMU and wheel odometry data for robust SLAM and obstacle avoidance. \nOptimize and benchmark models on Jetson-class edge devices with TensorRT / ONNX Runtime. \nCollect, 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.\n\nRequirements\nSolid grasp of linear algebra, probability and geometry; coursework or projects in CV or robotics perception. \nProficient 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. \n\nFamiliarity with deep-learning vision (PyTorch or TensorFlow)-classification, detection or segmentation. \nHands-on work with point-cloud processing (PCL, Open3D); know when to apply voxel grids, KD-trees, RANSAC or ICP. \nBonus: exposure to camera-LiDAR calibration, or real-time optimization libraries (Ceres, GTSAM).Preferred Skills:\n\nPython 3.x \nC++17/20 \nROS 2 \nPyTorch \nOpen3D \nRANSAC \nBenefits\nFor apprentice/Intern :\nThis is a six-month contract-to-hire position, with potential for longer-term opportunities depending on your contributions and interests. 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