Menlo Research

Researcher, World Models

San Francisco

Sponsorship not specifiedDetected 12 days ago

Full-Stack DevelopmentMachine LearningPyTorchComputer VisionRoboticsSensorsResearchCommunicationCollaboration

About 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.

Design, train, and rigorously evaluate world models that let Asimov predict the consequences of actions across visual, proprioceptive, and force/torque modalities.
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.
This is a rare seat where your research runs on real hardware in short cycles, your data and modeling choices are yours to own, and your work ships in the open.
They use it to think better, and make their work easier for others to build on.

you have trained models and can show solid, honest evaluations, not just training curves.
Proven modeling track record: you have trained models and can show solid, honest evaluations, not just training curves.

Publications at NeurIPS, ICML, ICLR, CoRL, or RSS (or arXiv work with comparable citations).
Not required with a strong portfolio.
Demonstrated hardware or robotics interest or hands-on experience.
Strong communication: technical blogs, talks, or clear written research.
World models are the bet that lets a humanoid generalize instead of memorize.
If you want the distance between an idea and a walking robot to be measured in weeks, this is the room.
You don't need deep AI expertise for every role, but we do expect everyone at Menlo to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work.
For some roles, AI fluency is a core requirement.

familiarity with prior and adjacent work, including VLA (vision-language-action) models, and a view on their trade-offs.
strong depth in at least one sensory domain (vision, audio, natural language, or similar).
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).

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.

This listing is sourced directly from Menlo Research's careers page and normalized into a canonical job model.