Robot Learning Engineer

About Origin

Origin is building physical AI for the built world. Our robots autonomously finish building interiors at production quality. OG-1 is deployed on live NYC commercial construction sites today. Backed by Accel.

Our system runs a Multi Agent Action Expert architecture: classical precision algorithms orchestrated alongside learned policies. The job is systematically expanding the learned components while keeping the system production-safe.

The Role

You own the full lifecycle of learned components on OG-1: from data collection and model training through edge deployment on Jetson AGX Orin. Every research project will have a deployment milestone. This is not a lab position.

What You Will Do

• Train and deploy VLA models for contact-rich manipulation using our imitation learning infrastructure.
• Build the data flywheel: teleoperation pipelines (GELLO, SpaceMouse, VR), DAgger-style online correction, demonstration curation.
• Research and prototype world models for surface state prediction, spray dynamics, and anomaly detection.
• Design offline evaluation metrics that predict real-world finishing quality before deployment.
• Optimize models for edge: TensorRT compilation, latency profiling, memory budgeting on dual Jetson AGX Orin.
• Hands-on experience with world models, including building or working with predictive or generative environment models (e.g., latent