Robotics Researcher, Locomotion

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    "description": "<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt; font-weight: bold\">About Menlo</span></p>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt\">Menlo Research is an Applied R&amp;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.</span></p>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt\"> </span></p>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt; font-weight: bold\">The Role</span></p>\n<p>We are building the motion intelligence that lets Asimov walk, recover, climb stairs, and carry loads without falling over. As a Robotics Researcher in Locomotion, you will work on the Cyclotron team -- Menlo's locomotion training pipeline -- developing the controllers and learned policies that run on physical bipedal hardware. You will train in simulation, close the sim-to-real gap, and deploy to the robot. The bar is real-world robustness, not benchmark performance.</p>\n<p><br></p>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt; font-weight: bold\">What You Will Do</span></p>\n<ul>\n<li>Research, develop, and iterate on locomotion controllers and motion policies for a bipedal humanoid</li>\n<li>Train and evaluate policies in Uranus, Menlo's in-house simulation engine, across a wide range of behaviors including walking, recovery, stair climbing, and load-bearing</li>\n<li>Design reward functions, curriculum schedules, and training infrastructure that produce policies robust enough for real-world deployment</li>\n<li>Drive systematic sim-to-real transfer and hardware iteration</li>\n<li>Integrate locomotion outputs with the broader Asimov autonomy stack</li>\n<li>Collect and analyze hardware telemetry to guide policy improvement</li>\n<li>Contribute to open-source releases of locomotion research and Cyclotron tooling<br></li>\n</ul>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt\"> </span></p>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt; font-weight: bold\">What You Will Bring</span></p>\n<ul>\n<li>Strong foundations in reinforcement learning, optimal control, and rigid body dynamics</li>\n<li>Hands-on experience training and deploying locomotion or motion control policies on physical legged robots</li>\n<li>Proficiency in Python; strong experience with JAX or PyTorch</li>\n<li>Experience with physics simulation environments such as MuJoCo, Isaac Gym, Genesis, or equivalent</li>\n<li>Practical track record closing the sim-to-real gap on a real platform</li>\n<li>Ability to iterate fast, instrument failures, and make data-driven improvements<br></li>\n</ul>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt\"> </span></p>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt; font-weight: bold\">Nice to Have</span></p>\n<ul>\n<li>Prior work specifically on bipedal or humanoid locomotion</li>\n<li>Experience with whole-body control, model predictive control, or loco-manipulation</li>\n<li>Familiarity with motion capture or real-time state estimation pipelines</li>\n<li>Publications at RSS, ICRA, CoRL, or equivalent venues<br></li>\n</ul>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt\"> </span></p>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt; font-weight: bold\">Why Join Menlo</span></p>\n<p><span style=\"font-family: arial, helvetica, sans-serif; font-size: 12pt\">This is applied robotics research with real stakes -- your code runs on a physical humanoid. We open-source aggressively, so your contributions reach the broader community. You will work alongside researchers and engineers across the full stack, in a team that values shipping over presenting. Competitive compensation and equity.</span></p>",
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