Researcher, World Models

About Menlo

Menlo Research is an Applied R&D lab building Asimov, an open-source humanoid robot platform, and the full software stack that powers it. Our mission is to make humanoid labor economically viable, turning software into physical labor at scale. We build across the full stack: hardware architecture, locomotion, autonomy, simulation, and infrastructure. We move fast, ship to real robots, and open-source everything we can. If you want your work to matter beyond a paper or a demo, this is the place.

The Role

We are hiring a Researcher to advance the world models at the core of Asimov's ability to perceive, predict, and act. You will work at the intersection of self-supervised representation learning, predictive architectures, and embodied control, in close collaboration with our platform, firmware, and hardware teams.

What You'll Do

• Design, train, and rigorously evaluate world models that let Asimov predict the consequences of actions across visual, proprioceptive, and force/torque modalities.
• Advance our self-supervised learning stack for visual and sensor representations, building on and extending the JEPA family (V-JEPA, I-JEPA, and related predictive-embedding approaches).
• Prototype and benchmark generative and predictive architectures (diffusion, DiT, flow matching, VAEs) against JEPA-style objectives for embodied prediction and planning.
• Own the data pipeline for your experiments end to end: curation, tooling, and scaling, without depending on a separate data-engineering team to move.
• Integrate what you build with our platform, firmware, and software teams so research reaches the robot, not just the paper.
• Contribute to sim-to-real transfer, inverse dynamics, and multi-modal sensor fusion, and publish or open-source work where it strengthens the field and the team.

What We Look For

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