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.
