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# Founding AI Research Engineer - Robot Learning

- **Company:** ORIGINS, LLC
- **Location:** San Francisco, CA, United States
- **Contract:** Permanent contract
- **Skills:** Nvidia CUDA, Software Debugging, Middleware, Python (Programming Language), Language Modeling, Open Source Technology, Pytorch, ONNX (Open Neural Network Exchange) Format, TensorRT
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/founding-ai-research-engineer-robot-learning-10xconstruction-ai-8023839

## About the Role

* BS/MS/PhD in CS, Robotics, ML, or equivalent experience shipping learned systems on physical robots.
 * Strong Python and PyTorch; comfort modifying research codebases (you'll work directly with open-source VLA implementations).
 * Experience in at least two of: imitation learning, RL, vision-language models, robot learning from demonstration, sim-to-real.
 * Track record deploying ML on real hardware: not just training to convergence, but debugging why the policy fails on the actual robot.
 * Working knowledge of ROS2 or equivalent robotics middleware.
 * Experience working with Simulation Systems like Isaac Sim.
 * GPU profiling and optimization (TensorRT, ONNX, CUDA); you understand why 200ms policy latency kills contact control.

## Description

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. 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., * 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.
 * Design the interface where learned policies propose actions and deterministic safety layers enforce constraints., * Hands-on with VLA architectures (π0/π0.5, OpenVLA, RT-2, Octo) or foundation model fine-tuning for robotics.
 * Teleoperation data collection and DAgger/HG-DAgger pipelines.
 * World model architectures (DreamerV3, V-JEPA, latent dynamics models).
 * Construction, manufacturing, or contact-rich industrial domains.
 * Publications at CoRL, RSS, ICRA, NeurIPS: valued but equivalent shipped work counts.


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