Forward Deployed Research Engineer - Menlo

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 robotics is not building a compelling prototype. It is making robotic systems deployable, repeatable, and economically useful in the real world. The Forward Deployed Research Engineer is a new kind of role at Menlo . It combines the strengths of a Forward Deployed Engineer and a Research Engineer. You will work directly on real customer problems, but you will not stop at integration or customization. You will use deployment pressure to uncover missing capabilities, design evaluations, collect data, adapt models, and turn one-off field learnings into reusable product and research improvements. This is not a support role. It is not solutions engineering. It is a deployment-native R&D role for people who want to stay close to reality and build the abstractions that make the next deployment easier.

What You'll Do

Own real customer and deployment problems end to end, from understanding the workflow to diagnosing failures in the field

Work directly with robotic systems in commercial and industrial environments where variability, ambiguity, and operational constraints are the norm

Translate deployment friction into research and product questions: what capability is missing, what data is needed, what evaluation should exist, what part of the stack must improve

Build and adapt systems across the deployment loop, including data collection, task-specific fine-tuning, and evaluation design

Collaborate closely with core research and platform teams so field learnings become reusable capabilities instead of one-off fixes

Contribute domain expertise to a broader forward deployment practice where knowledge is shared across deployments and specializations

Help define the operating model for how humanoid systems are deployed, improved, and scaled

What We're Looking For

Deep expertise in at least one relevant technical domain: perception, navigation, manipulation, or teleoperation

Experience deploying AI, robotics, or embodied systems in real environments rather than only in lab settings

Comfortable working outside your specialization when the deployment demands it

Experience collecting, cleaning, or curating deployment data for model improvement

Experience designing evaluations or benchmarks for systems that interact with real-world environments

Able to explain complex technical concepts clearly to bot