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 Indias most talent-dense robotics team consisting of individuals from IITs, Stanford, UCLA, etc.

About the Role :

You will work on building and optimizing 3D perception systems that enable robots to understand and interact with complex real-world environments. The goal is to develop robust perception pipelines that work reliably across both simulation and real-world construction sites, ensuring accurate scene understanding, localization, and decision-making.

Key Responsibilities :

3D Perception Development & Scene Understanding :

- Design, implement, and deploy realtime 3D perception pipelines leveraging LiDAR, IMU, Stereo, and RGB cameras.

- Develop algorithms for spatial and temporal data interpretation to enable high-fidelity semantic scene understanding.

- Optimize ego-motion estimation and localization modules to ensure seamless integration with downstream planning and control tasks.

Deep Learning :

- Train and integrate deep learning models required for semantic world understanding and surface finish classification for quality control.

- Collect and curate high-quality datasets (real and synthetic) and automate training pipelines and experiment tracking.

- Benchmark and optimize perception models for edge devices to ensure real-time performance in resource-constrained environments.

Sensor Fusion & Localization :

- Design and implement sensor fusion strategies combining visual, inertial, and spatial data.

- Architect and implement sophisticated sensor fusion strategies that integrate classical methods with deep learning approaches to convert noisy, asynchronous data from heterogeneous sensors into a unified environment representation.

Calibration :

- Develop and automate robust extrinsic and intrinsic calibration procedures (Camera, LiDAR, IMU) using target-based and/or targetless methods.

- Design and implement algorithms for online calibration drift detection and self-healing to maintain system integrity during long-term deployments.

- Establish rigorous quantitative metrics to objectively evaluate and certify calibration quality.

Collaboration :

- Partner with Navigation, Manipulation, and Cloud teams to ensure perception outputs are optimized for downstream path planning, grasping, and remote fleet monitoring.

- Define, track system-level and own system level KPIs and perception metrics to identify regressions across software iterations.