Robotics systems engineer

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.

As a Robotic Systems Engineer
, you will own critical layers of the humanoid robot stack — spanning embedded firmware, middleware, controls, and system integration. You’ll bridge low-level hardware interfaces with high-level behavioral systems, ensuring our robots operate safely, reliably, and efficiently in real-world environments.

This is a deeply hands-on role for an engineer who thrives at the intersection of embedded systems and large-scale robotic software. You’ll work across hardware, controls, perception, and ML teams to transform research behaviors into production-grade deployments — building the core systems that serve as the nervous system and coordination layer of our humanoids.

• Design and maintain embedded firmware, low-level drivers, and real-time communication interfaces for sensors and actuators.
• Develop middleware, state machine architectures, and distributed control frameworks coordinating robot behavior.
• Build and optimize control interfaces bridging research algorithms with deployed hardware (motion, manipulation, locomotion).
• Implement safety systems, fail-safes, and recovery mechanisms for real-world humanoid deployments.
• Lead board bring-up, hardware/software integration, and system validation in collaboration with hardware teams.
• Develop telemetry, monitoring, and debugging infrastructure for deployed robots.
• Create robust testing and validation frameworks to ensure production reliability and continuous improvement.
• Interface with deployment and operations teams to diagnose field issues, patch live systems, and maintain uptime.

• 5+ years of experience in robotics, embedded systems, autonomous systems, or large-scale hardware/software integration.
• Strong proficiency in C++ and Python; solid experience with C for embedded systems.
• Deep familiarity with ROS2, middleware design, distributed systems, and control architectures.
• Experience with microcontrollers, embedded Linux, or RTOS platforms.
• Hands‑on experience with communication protocols (CAN, SPI, I2C, UART, Ethernet).
• Strong systems‑level debugging skills across hardware and software boundaries.
• Demonstrated ability to integrate research code into safety‑critical, real‑world robotic systems.

• Experience with teleoperation, VR interfaces, or remote robot control systems.
• Background in robot learning, behavior trees, motion planning, or multi‑robot coordination.
• Experience with motor control, safety‑critical embedded systems, or real‑time optimization.

• Ownership over the embedded and middleware systems that make humanoid robots safe and deployable at scale.
• The ability to ship new behaviors and firmware to live robots within weeks, not quarters.
• Early equity with meaningful upside in a venture‑backed robotics company.
• Deep exposure across the full robotics stack — hardware, controls, perception, ML, and fleet operations.
• A foundational role in scaling embodied intelligence from research prototypes to large‑scale deployment.

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