Humanoid

Lead firmware development for Humanoid’s next-generation humanoid robots, focusing on real-time motion control, stabilization, sensor integration, and embedded communication. This staff-level role combines robotics, embedded systems, and real-time algorithms while mentoring engineers and influencing core platform initiatives.

Lead Firmware Engineer building high-performance embedded software and real-time control systems for humanoid robots. The role combines hands-on firmware development with technical leadership across robotics, hardware integration, and motion control.

Design and develop hard-real-time embedded software and firmware that controls Humanoid’s humanoid robots. You’ll work across motion control, sensors, actuators, communication networks, and hardware-software integration to deploy reliable robotic systems in real-world industrial environments.

Own the build system and CI infrastructure that powers Humanoid’s multi-target robotics engineering organization. You’ll improve build speed, reliability, caching, developer environments, and feedback loops across firmware, robot software, simulation, and cloud.

Senior Software Controls Engineer responsible for measuring and improving control quality across humanoid robots, replacing subjective assessments with reproducible metrics, automated evaluation, and fleet-level dashboards. The role combines robotics software engineering, test infrastructure, and data-driven validation across simulation and hardware.

Firmware Engineer developing embedded software, drivers, hardware integrations, and OTA infrastructure for humanoid robot end effectors and operator-worn devices. The role sits at the intersection of firmware, electrical, and mechanical engineering across sensors, microcontrollers, and Linux-based compute platforms.

Build the cloud platform and software services that manage Humanoid’s fleet of commercially deployed humanoid robots. This full-stack role spans backend systems, web applications, robot-side services, infrastructure, observability, and testing.

Develop reinforcement learning policies that enable dynamic locomotion and loco-manipulation for commercially deployed humanoid robots. This hands-on role combines large-scale simulation, sim-to-real transfer, and real-hardware experimentation.