What are the responsibilities and job description for the Researcher, World Models position at ChatGPT Jobs?
Job Description
Job Description: Researcher – World Models
Location: San Francisco, CA
About Menlo Research
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.
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.
Labor & Employment Law
What You'll Do
World models are the bet that lets a humanoid generalize instead of memorize. 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.
Machine Learning & Artificial Intelligence
A Note on AI
We expect everyone at Menlo to be intellectually curious, drawn to tinkering, and excited to use AI as a real collaborator. AI fluency is a core requirement for some roles, stated explicitly in qualifications.
Equal Opportunity
We hire talented people from a wide range of backgrounds. Menlo Research is an equal opportunity employer and provides reasonable accommodations during the application process.
Job Description: Researcher – World Models
Location: San Francisco, CA
- Remote
About Menlo Research
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.
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.
Labor & Employment Law
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 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.
- Integrate what you build with our platform, firmware, and software teams so research reaches the robot.
- Contribute to sim-to-real transfer, inverse dynamics, and multi-modal sensor fusion, and publish or open-source work where it strengthens the field.
- Proven modeling track record: trained models with solid, honest evaluations.
- JEPA fluency: understanding of joint-embedding predictive approach and its alternatives.
- Breadth across approaches: familiarity with VLA models and trade-offs.
- Depth in a modality: strong depth in vision, audio, natural language, or similar.
- Strong data abilities: ability to work without a data-engineering team.
- Solid engineering: ability to implement, integrate, and ship alongside teams.
- Conversant, ideally deep, in several of: SSL for visual/sensor representations; world models (JEPA variants); generative/predictive architectures; robotics ML (VLA, inverse dynamics, sim-to-real, optical flow); sensor fusion; PyTorch, JAX, distributed training.
- Publications at NeurIPS, ICML, ICLR, CoRL, RSS (or arXiv with comparable citations).
- PhD or equivalent research experience in ML, robotics, or computer vision (not required with 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. 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.
Machine Learning & Artificial Intelligence
A Note on AI
We expect everyone at Menlo to be intellectually curious, drawn to tinkering, and excited to use AI as a real collaborator. AI fluency is a core requirement for some roles, stated explicitly in qualifications.
Equal Opportunity
We hire talented people from a wide range of backgrounds. Menlo Research is an equal opportunity employer and provides reasonable accommodations during the application process.