mundane
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 an
Engineering Manager
on the
Embodied Systems
team, you will own the highest-leverage, multi-disciplinary programs that sit at the heart of Mundane’s robot deployment stack. You’ll drive structure, predictability, and velocity across the company—spanning robot architecture, controls, teleoperation, safety systems, fleet operations, and data pipelines.
This is a
deeply technical, high-ownership role
for someone who thrives on orchestrating complex systems and aligning world-class engineers toward shared execution goals. You will define program strategy, design engineering processes, lead cross-team initiatives, and personally dive into logs, field tests, and bring-ups to ensure our robots operate with production-grade reliability.
You’ll shape the frameworks that allow humanoid robots to scale from dozens to hundreds to thousands. Your decisions will directly influence deployment cadence, learning velocity, safety standards, and engineering efficiency across the entire company.
Responsibilities
Lead multi-quarter, company-critical programs across controls, perception, teleoperation, networking, safety, and hardware integration.
Architect execution frameworks, program structures, and reliability validation processes for large-scale multi-robot deployment.
Translate high-level strategic goals into technical requirements, system milestones, and detailed engineering roadmaps.
Establish disciplined release management, version control workflows, and readiness gates for pushing updates to the humanoid fleet.
Oversee robot bring-up lifecycles, sensor + actuator validation, calibration workflows, and system-level regression testing.
Drive root-cause analysis across hardware, software, middleware, and networked systems—coordinating teams to closure.
Create scalable telemetry, reliability tracking, and field operations dashboards to measure system performance at fleet scale.
Partner with ML, controls, and perception teams to integrate new models, ensuring production stability and predictable behavior.
Serve as an engineering \'force multiplier\' — unblocking teams, clarifying decisions, aligning priorities, and creating execution cohesion.
Represent Embodied Systems in cross-company strategy discussions, bridging research ambitions with deployment realities.
Qualifications
7+ years of experience in robotics, autonomous systems, embedded systems, or large-scale technical program management.
Demonstrated success leading complex system programs across multiple engineering disciplines.
Strong technical fluency: ROS/ROS2, distributed systems, middleware, networking, sensors, controls, hardware/software integration.
Hands‑on comfort working with robotic platforms: reading logs, inspecting bag files, orchestrating test runs, and guiding debugging.
Proven ability to design engineering processes that improve reliability, velocity, and cross-team coordination.
Excellent communication and leadership skills, especially in high-speed, ambiguity-heavy environments.
Experience working with or supporting field deployments of hardware systems is a major plus.
Bonus
Experience building or managing teleoperation, VR remote control, or low-latency networking systems.
Background in motion planning, real-time control, robot learning, or ML infrastructure.
Experience scaling robotic or autonomous vehicle systems across large fleets.
What You’ll Get
Ownership of some of the most strategically important programs at the company.
The ability to shape the execution rhythms, reliability practices, and scaling frameworks for humanoid deployment.
Early equity with meaningful upside in a venture-backed robotics company.
The chance to push updates and capabilities to live robots in weeks, not quarters.
Deep technical exposure across hardware, controls, perception, ML, fleet operations, and real-world deployments.
A foundational role in defining how embodied intelligence scales from the lab into the real world.
Our Privacy Policy: https://airtable.com/appJtaRURYFPJILxd/pagQU1ETKJQ99g5Ge/form
Referrals increase your chances of interviewing at Mundane by 2x.
#J-18808-Ljbffr
About the Role As an
Engineering Manager
on the
Embodied Systems
team, you will own the highest-leverage, multi-disciplinary programs that sit at the heart of Mundane’s robot deployment stack. You’ll drive structure, predictability, and velocity across the company—spanning robot architecture, controls, teleoperation, safety systems, fleet operations, and data pipelines.
This is a
deeply technical, high-ownership role
for someone who thrives on orchestrating complex systems and aligning world-class engineers toward shared execution goals. You will define program strategy, design engineering processes, lead cross-team initiatives, and personally dive into logs, field tests, and bring-ups to ensure our robots operate with production-grade reliability.
You’ll shape the frameworks that allow humanoid robots to scale from dozens to hundreds to thousands. Your decisions will directly influence deployment cadence, learning velocity, safety standards, and engineering efficiency across the entire company.
Responsibilities
Lead multi-quarter, company-critical programs across controls, perception, teleoperation, networking, safety, and hardware integration.
Architect execution frameworks, program structures, and reliability validation processes for large-scale multi-robot deployment.
Translate high-level strategic goals into technical requirements, system milestones, and detailed engineering roadmaps.
Establish disciplined release management, version control workflows, and readiness gates for pushing updates to the humanoid fleet.
Oversee robot bring-up lifecycles, sensor + actuator validation, calibration workflows, and system-level regression testing.
Drive root-cause analysis across hardware, software, middleware, and networked systems—coordinating teams to closure.
Create scalable telemetry, reliability tracking, and field operations dashboards to measure system performance at fleet scale.
Partner with ML, controls, and perception teams to integrate new models, ensuring production stability and predictable behavior.
Serve as an engineering \'force multiplier\' — unblocking teams, clarifying decisions, aligning priorities, and creating execution cohesion.
Represent Embodied Systems in cross-company strategy discussions, bridging research ambitions with deployment realities.
Qualifications
7+ years of experience in robotics, autonomous systems, embedded systems, or large-scale technical program management.
Demonstrated success leading complex system programs across multiple engineering disciplines.
Strong technical fluency: ROS/ROS2, distributed systems, middleware, networking, sensors, controls, hardware/software integration.
Hands‑on comfort working with robotic platforms: reading logs, inspecting bag files, orchestrating test runs, and guiding debugging.
Proven ability to design engineering processes that improve reliability, velocity, and cross-team coordination.
Excellent communication and leadership skills, especially in high-speed, ambiguity-heavy environments.
Experience working with or supporting field deployments of hardware systems is a major plus.
Bonus
Experience building or managing teleoperation, VR remote control, or low-latency networking systems.
Background in motion planning, real-time control, robot learning, or ML infrastructure.
Experience scaling robotic or autonomous vehicle systems across large fleets.
What You’ll Get
Ownership of some of the most strategically important programs at the company.
The ability to shape the execution rhythms, reliability practices, and scaling frameworks for humanoid deployment.
Early equity with meaningful upside in a venture-backed robotics company.
The chance to push updates and capabilities to live robots in weeks, not quarters.
Deep technical exposure across hardware, controls, perception, ML, fleet operations, and real-world deployments.
A foundational role in defining how embodied intelligence scales from the lab into the real world.
Our Privacy Policy: https://airtable.com/appJtaRURYFPJILxd/pagQU1ETKJQ99g5Ge/form
Referrals increase your chances of interviewing at Mundane by 2x.
#J-18808-Ljbffr