Deployment Engineer

Menlo; Palo Alto (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Menlo seeks a Deployment Engineer to tackle real customer and deployment problems end to end, from workflow understanding to field diagnostic failures. You will work directly with robotic systems in real environments where variability and constraints are the norm.

This role emphasizes turning deployment friction into research questions and building reusable capabilities across the stack. You will collaborate with core research and platform teams to translate field learnings into scalable

Qualifications

• Deep expertise in at least one technical domain: perception, navigation, manipulation, or teleoperation.
• Experience deploying AI, robotics, or embodied systems in real environments.
• Comfortable working outside your specialization when 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 both technical and non-technical audiences.
• Energized by ambiguity, motivated by ownership, and wants to see work survive contact with the real world.

Responsibilities

• 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

Skills

Perception

Navigation

Manipulation

Teleoperation

AI deployment

Robotics in real envs

Communication

Ambiguity tolerance

Job description

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. 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 both technical and non-technical audiences

• Energized by ambiguity, motivated by ownership, and wants to see work survive contact with the real world

Nice to Have

• Comfort moving between software, research, operations, and user conversations as needed

• Evidence of building trust with users while maintaining a strong technical point of view

• Prior experience in a forward deployed or customer-facing technical role at a fast-moving company

Why Join Menlo?

You will sit at the point where all of Menlo’s core systems come together: the agent platform, simulation infrastructure, motor control and policy training, the Asimov reference platform, and the data engine. If you join as a Deployment Engineer, you will not just fill a role. You will help define a category. If you want to do serious technical work, stay close to real deployments, and invent the operating model for deployable robotic systems, we would love to talk.

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.

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.

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.

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. 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 both technical and non-technical audiences

• Energized by ambiguity, motivated by ownership, and wants to see work survive contact with the real world

Nice to Have

• Comfort moving between software, research, operations, and user conversations as needed

• Evidence of building trust with users while maintaining a strong technical point of view

• Prior experience in a forward deployed or customer-facing technical role at a fast-moving company

Why Join Menlo?

You will sit at the point where all of Menlo’s core systems come together: the agent platform, simulation infrastructure, motor control and policy training, the Asimov reference platform, and the data engine. If you join as a Deployment Engineer, you will not just fill a role. You will help define a category. If you want to do serious technical work, stay close to real deployments, and invent the operating model for deployable robotic systems, we would love to talk.

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.

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.

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.