Founding Research Scientist, Robot Learning

GRAM is a self-replication company creating populations of insectoids for the physical economy. The Founding Research Scientist will own the robot-learning research agenda, set technical direction and evaluation standards, develop general models and policies for physical behavior, and lead the growth of the research program.

Responsibilities:

• Develop, pretrain, and adapt robot foundation models that acquire reusable physical capabilities from heterogeneous experience
• Set the research roadmap, technical standards, and experimental decision process for GRAM's robot-learning program
• Design representations, objectives, architectures, and adaptation methods that transfer across robot morphology, sensor configuration, task, environment, tool, and machine variation
• Build training curricula from heterogeneous physical and simulated experience, with strict dataset and checkpoint lineage
• Scale experiments in PyTorch or JAX while separating gains from model architecture, objective, data composition, compute, initialization, and evaluation leakage
• Define frozen evaluations and falsifiable capability claims for task transfer, environmental robustness, embodiment transfer, data efficiency, latency, and recovery
• Deploy selected models through C++ robotics runtimes, then use physical failures and offline-to-online discrepancies to determine the next research question
• Help recruit, evaluate, and mentor the researchers and engineers who extend the program