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 The hard problem in simulation is not building a demo environment. It is building digital twins that are faithful enough to train policies, close sim-to-real gaps, and accelerate hardware development at scale. As a Software Engineer, Digital Twin, you will own the environments, tooling, and pipelines that make Asimov's virtual counterpart a first-class engineering asset. You will work across MuJoCo, Isaac Sim, and Unreal Engine -- using the right tool for the right layer of the stack, from physics training to photorealistic synthetic data generation. What You Will Do - Build and maintain high-fidelity digital twin environments for Asimov across MuJoCo, Isaac Sim, and Unreal Engine, calibrated to real hardware behavior. - Design and own the systems -- not just the environments -- that let locomotion, autonomy, and perception teams generate, validate, and iterate on simulation scenarios at scale. - Build pipelines for asset import, USD and MJCF workflows, sensor modeling, and real-to-sim calibration to keep digital twins synchronized with evolving hardware. - Develop photorealistic rendering pipelines in Unreal Engine for synthetic data generation and perception model training. - Work with hardware and mechatronics teams to model actuator dynamics, contact physics, and structural behavior, ensuring simulation parameters reflect physical ground truth. - Integrate digital twin environments with Menlo's locomotion training pipeline (Cyclotron) and autonomy stack, enabling teams to run experiments and close the sim-to-real gap. - Contribute to the open-source Asimov simulation stack, including tooling, documentation, and reproducible environment workflows. What You Will Bring - Hands-on experience building or maintaining simulation environments in MuJoCo, Isaac Sim, or a comparable physics engine -- on real robot development programs, not just coursework. - Proficiency in Python and C++. - Solid understanding of rigid body dynamics, contact simulation, and how simulator parameters translate to physical hardware behavior. - Experience building the systems that enable simulation at scale: procedural generators, validation pipelines, CI hooks, or environment tooling. - Familiarity with ROS2 and common robotics data formats. Nice to Have - Unreal Engine experience for robotics simulation or synthetic data pipelines. - Prior work on sim-to-real transfer for legged locomotion or dexterous manipulation. - Experience with USD, URDF, or MJCF asset workflows. - Exposure to domain randomization, physics parameter tuning, or reality-gap analysis. - Open-source contributions to robotics or simulation projects. Why Join Menlo The environments you build are not test fixtures. They are where every new locomotion policy, autonomy behavior, and hardware iteration is born before it touches a real robot. You will have direct collaboration with locomotion, autonomy, and hardware teams -- short feedback loops, high visibility, and real stakes. We open-source aggressively. If you want your simulation work to matter in the real world, this is where to do it. A Note on AI 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. When that's the case, we'll say so explicitly in the qualifications. People who thrive here don't treat AI as a novelty. They use it to think better, and make their work easier for others to build on. Equal Opportunity and Accommodations We hire talented people from a wide range of backgrounds. If you're excited about a role but don't meet every bullet, we still encourage you to apply. Menlo Research is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Menlo provides reasonable accommodations during the application process. If you need one, please let your recruiter know.