Menlo Research
Forward Deployed Engineer
San Francisco
Sponsorship not specifiedDetected 35 days ago
Full-Stack DevelopmentRoboticsResearch
About the role
- 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.
Responsibilities
- Own real customer and deployment problems end to end, from understanding the workflow to diagnosing failures in the field
- 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
- Evidence of building trust with users while maintaining a strong technical point of view
Requirements
- 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
- Experience collecting, cleaning, or curating deployment data for model improvement
- Experience designing evaluations or benchmarks for systems that interact with real-world environments
- Comfort moving between software, research, operations, and user conversations as needed
- Prior experience in a forward deployed or customer-facing technical role at a fast-moving company
- 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.
Company info
- 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.
- 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
- What We're Looking For
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This listing is sourced directly from Menlo Research's careers page and normalized into a canonical job model.