Perception Engineer

Origin; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Origin is hiring a Perception Engineer to empower autonomous drywall-finishing robots with vision and scene understanding. You will implement perception pipelines, fuse camera and LiDAR data, and drive real-time localization for dynamic construction sites.

Join a team blending physics-based robotics with deep learning, deploying on edge hardware and collaborating across robotics groups to ship production-grade perception stacks.

Qualifications

• Strong background in robotics perception or computer vision.
• Experience with ROS 2 nodes, message systems, and launches.
• Proficiency in Python and C++ for real-time pipelines.
• Hands-on with 3D data: point clouds, depth maps, and sensors.

Responsibilities

• Develop and deploy 3D perception components using depth sensors and LiDAR.
• Build ROS 2 nodes to process spatial data for environment modeling.
• Train and integrate deep-learning models for 3D understanding.
• Design sensor fusion strategies for scene reconstruction and localization.
• Benchmark models for edge deployment (Jetson) using TensorRT/ONNX.
• Collaborate with robotics teams to deliver production-ready stacks.

Skills

Python

C++

ROS 2

PyTorch

Open3D

PCL

Job description

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.
• Build ROS 2 nodes that 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, including surface analysis and object segmentation.
• 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.
• Collaborate across robotics teams (manipulation, navigation, cloud) to deliver production-ready perception stacks for autonomous operation in dynamic construction environments.

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 optimization libraries (Ceres, GTSAM).

Good to have:

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