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 We are building the sensory substrate that lets Asimov understand its environment. As a Robotics Researcher in Perception and Vision, you will own the pipeline from raw sensor data through object detection, 3D scene understanding, and semantic representation -- producing the outputs that downstream planning and manipulation systems depend on. Your models run on the robot, in real time, in the real world. Closing the sim-to-real gap is not someone else's problem; it is core to this role. What You Will Do - Design, train, and deploy perception systems for object detection, segmentation, depth estimation, and 3D scene reconstruction - Build multi-modal pipelines that fuse RGB, depth, and inertial data into robust real-time representations - Develop and scale vision models that transfer reliably from Uranus to physical hardware - Optimize inference pipelines for performance constraints on embedded compute - Work closely with navigation and manipulation teams to ensure perception outputs meet downstream requirements - Drive systematic evaluation on hardware and iterate on failure modes - Contribute to open-source releases of perception models and tooling What You Will Bring - Deep foundations in computer vision, 3D geometry, and deep learning - Hands-on experience building and deploying perception systems on physical robots or real-time embedded platforms - Proficiency in Python and C++; strong experience with PyTorch or JAX - Track record taking perception models from research prototype to deployed inference - Experience with sensor fusion across camera, depth, and inertial modalities - Practical instincts for understanding why models break in the real world Nice to Have - Experience with vision-language models, open-vocabulary detection, or embodied scene understanding - Familiarity with NeRF, Gaussian splatting, or differentiable rendering approaches - Prior work on manipulation or mobile robotics perception - Publications at CVPR, ICCV, ECCV, CoRL, or equivalent venues Why Join Menlo 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. 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.