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Mundane is a venture-backed seed-stage robot learning startup founded by a team of Stanford researchers and builders. We’re deploying a massive fleet of humanoid robots to perform mundane tasks in commercial environments, collecting data to build the next generation of embodied intelligence. We’re a fast-paced, execution-driven team of engineers, roboticists, and dreamers.

About the Role

As VP of Embodied Systems , you’ll bridge the gap between research and deployment — owning the systems, infrastructure, and processes that turn experimental robot behaviors into production-ready capabilities. You’ll lead efforts in systems integration, fleet management, networking, and large-scale testing to ensure our humanoid robots perform reliably across dynamic environments.

You’ll be the connective tissue between R&D and real-world deployment — building the frameworks that make learning-driven robotics scalable, safe, and measurable. This is a hands-on leadership role: you’ll architect the deployment stack, guide cross-functional teams, and shape the strategy for how Mundane brings embodied intelligence into the wild.

Responsibilities

• Oversee the transition of robot learning research into robust deployable systems across our humanoid fleet.
• Design and implement frameworks for fleet management, network reliability, and real-time monitoring .
• Lead systems integration across software, hardware, and cloud infrastructure to ensure seamless operation.
• Develop and maintain testing pipelines and simulation-to-reality validation frameworks for large-scale deployments.
• Deep familiarity with ROS and middleware architectures , including custom node development, message passing, and distributed control.
• Collaborate with ML, controls, and perception teams to integrate new models into production robots.
• Drive the continuous improvement of field reliability, latency, and data collection efficiency.
• Build and manage a high-performing development and testing team, fostering tight feedback loops between research and deployment.
• Establish best practices for deployment safety, telemetry, and debugging in complex, multi-robot environments.

Qualifications

• 5+ years of experience in robotics, autonomous vehicles, or large-scale systems deployment .
• Proven track record in systems integration, fleet operations, or networked robotics .
• Strong programming experience in C++ and Python ; familiarity with ROS2 , distributed systems, and real-time data pipelines.
• Deep understanding of hardware/software integration , network architecture , and deployment automation .
• Experience leading technical teams and managing cross-functional development cycles.
• Exceptional debugging, reliability, and systems design skills.

Bonus:

• Experience with VR teleoperation or remote control systems.
• Background in robotic controls or motion planning .
• Familiarity with machine learning or robot learning frameworks .

What You’ll Get

• Ownership of the development stack powering humanoid deployment at scale.
• A leadership seat at the intersection of robotics research and production systems.
• Early equity with meaningful upside in a venture-backed robotics company.
• The ability to ship features to live robots in weeks, not quarters.
• Deep exposure to every layer of the stack — hardware, controls, perception, ML, and fleet ops.
• A chance to define how embodied intelligence moves from lab to world.

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