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.