Perception Engineer -Apprentice

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
• Optimise 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
  

Qualifications & Skills

• 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-learning vision** (PyTorch or TensorFlow)—classification, detection or segmentation
• Hands-on work with **point-cloud processing** (PCL, Open3D); know when to apply voxel grids, KD-trees, RANSAC or ICP
• Bonus: exposure to camera-LiDAR calibration, or real-time optimisation libraries (Ceres, GTSAM)
  

Why Join Us

• Work side-by-side with founders and senior engineers to redefine robotics in construction
• Build tech that replaces dangerous, repetitive wall-finishing labor with intelligent autonomous systems
• Help shape not just a product, but an entire company—and see your code on real robots at active job-sites
  

Requirements

• Python 3.x
• C++17/20
• ROS 2
• PyTorch
• Open3D
• RANSAC