Perception Engineer
At a glance
Mid-level AI Research role at Origin. Bengaluru · full-time.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build 3D scene-understanding components from depth sensors, LiDAR and RGB camera data
- Turn point clouds, depth maps and image streams into environment models that support task planning
- Train and connect neural models for 3D scene labeling and quality checks
- Combine visual, inertial and spatial inputs to reconstruct scenes and locate the robot
- Tune perception for edge computers, maintain sensor calibration and prepare datasets and training workflows
What you bring
- You have studied or built projects involving computer vision or robotics perception, with a foundation in geometry, probability and linear algebra
- You can develop in Python and C++, and have used ROS 2 with custom messages or launch configurations
- You have applied deep-learning vision methods and worked directly with point-cloud data
- You have exposure to sensor-calibration methods
Who this fits
This mid-level, full-time role is based on-site in Bengaluru. It suits an engineer focused on robot perception, including 3D vision, sensor fusion and deployment for autonomous operation.
From the employer
About Origin
Origin (previously 10xConstruction) is building general-purpose autonomous robots for US construction to tackle rising costs, safety risks, and labor 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 Engineer 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
- Develop and deploy 3D perception components for geometric scene understanding using depth sensors, LiDAR, and RGB cameras.
- Process and interpret spatial data (point clouds, depth maps, image streams) for environment modeling and task planning.
- Train and integrate deep-learning models for 3D semantic understanding and quality evaluation.
- Design robust sensor fusion strategies that combine visual, inertial, and spatial data for scene reconstruction and robot localization.
- Benchmark and optimize perception models for deployment on edge compute platforms (e.g., NVIDIA Jetson) using tools like TensorRT or ONNX.
- Collect and curate high-quality datasets (real and synthetic); automate training pipelines and experiment tracking.
- Perform and validate sensor calibration (camera, LiDAR, IMU) and develop checks to maintain calibration quality over time
- Collaborate across robotics teams (manipulation, navigation, cloud) to deliver production-ready perception stacks for autonomous operation in dynamic construction environments.
Requirements
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 ; know when to apply voxel grids, KD-trees, RANSAC or ICP.
- Exposure to sensor calibration algorithms,
Good to have:
- Experience with ROS 2
- Familiarity with PCL, Open3D
- Exposure to real-time optimization libraries (Ceres, GTSAM).