Ground every answer in facts on this page and the original listing. We never invent Glassdoor-style reviews or salaries that are not in our data.
Strong fit if you want hands-on research on world models in an on-site San Francisco setting at Menlo. Thin public company and compensation data means you should validate team focus, publication norms, and pay bands directly with the employer.
As a Researcher, World Models at Menlo in San Francisco, expect days centered on hypothesis-driven model work: reading papers, designing experiments on predictive or generative world models, running training or evaluation loops, and writing up results for internal review. Collaboration is typically with other researchers and engineers on metrics, datasets, and ablations rather than product support tickets.
No listed certifications map to this posting. Build depth in deep learning research practice, probabilistic modeling, simulation or embodied benchmarks where relevant, and clear experimental write-ups. Prioritize public research artifacts (papers, code, evals) over vendor cert paths for this title.
The listing marks remote as no; plan for San Francisco, California on-site or hybrid only if Menlo confirms otherwise.
Typical work is experimental research—designing models that predict or simulate environment dynamics, measuring progress rigorously, and iterating with peers.
No certification resources were provided for this family; hiring usually weighs research experience and technical depth over certs.
Researcher, World Models, Menlo, San Francisco, California Position Summary Meno Research is seeking a talented and innovative Researcher to join our team in developing advanced world models for Asimov, an open-source humanoid robot platform. The ideal candidate will have experience in building complex simulations and working at the intersection of hardware architecture, locomotion, autonomy, and infrastructure. Key Responsibilities Develop and maintain sophisticated world models to enhance Asimov's perception and decision-making capabilities Collaborate with cross-functional teams to integrate world models into the full software stack of Asimov Conduct research in areas such as computer vision, machine learning, and robotics to improve Asimov's performance Participate in regular code reviews and contribute to the continuous improvement of our simulation infrastructure Qualifications PhD or Master’s degree in Computer Science, Robotics, Electrical Engineering, or a related field Strong background in computer vision, machine learning, and robotics Experience with building complex simulations for robotic applications Familiarity with hardware architecture and real-time systems is a plus Excellent problem-solving skills and ability to work independently as well as part of a team Strong programming skills in Python, C++, or other relevant languages Why Join Menlo Joining Menlo means being part of an exciting and fast-paced environment where you can make significant contributions to the development of humanoid robots. Our mission is to transform software into physical labor at scale, and we value innovation, collaboration, and a commitment to excellence. Next Steps To apply, complete your application directly on this page, or you'll be redirected to the employer's application platform to finish submitting there.
Generated for personal interview prep · 2026-08-09 UTC · getajob.ai