Build the Cognitive Foundation With Us
We're looking for researchers who want to work on foundational problems in machine reasoning and task understanding—specifically for humanoid automation.
Open Research Roles
AI / Representation Learning Researcher
Core feasibility and model development
This role drives the core feasibility work—exploring whether task-level intent and long-horizon reasoning can be inferred from observation and abstracted into reusable representations.
ML research, applied AI, or data science with experience in temporal/sequential models.
Task Reasoning Engineer
Robotics-adjacent · Not hardware robotics
This role grounds our research in robotics-relevant task structure—ensuring our abstractions map to real-world execution without requiring control, kinematics, or hardware expertise.
AI planning, decision-making systems, or simulation engineering with exposure to task-level robotics problems.
What We're Building
We're exploring whether task-level intent and long-horizon reasoning can be inferred from observation and abstracted into a reusable intelligence layer.
If feasible, this capability would form the cognitive substrate for humanoid and flexible automation systems—enabling industrial actors to access advanced reasoning through standardized interfaces rather than vertically integrated solutions.
This is foundational research with real-world implications. We're at the stage where the right collaborators can shape the direction.
Interested in collaborating?
Reach out to discuss research directions, collaboration structures, or just to connect.