Apptronik is a human-centered robotics company developing AI-powered robots to support humanity in every facet of life. Our flagship humanoid robot, Apollo, is built to collaborate thoughtfully with people, starting with critical industries such as manufacturing and logistics, with future applications in healthcare, the home, and beyond. We operate at the cutting edge of embodied AI, applying our expertise across the full robotics stack to solve some of society's most important problems. You will join a team dedicated to bringing Apollo to market at scale, tackling the complex challenges like safety, commercialization, and mass production to change the world for the better.
JOB SUMMARY
As a Senior Software Engineer on the Autonomy team at Apptronik, you will design and deploy learning-driven, mission-level autonomy systems that enable humanoid robots to operate robustly in real-world human environments. Your work focuses on the coordination, execution, and adaptation of robot behaviors using learning-based approaches rather than hand-authored task planners.
You will build the software that allows humanoid robots to reason over goals, adapt to dynamic environments, and execute complex missions by integrating outputs from perception, navigation, manipulation, and control systems. This role sits at the intersection of autonomy research and production engineering, with a strong emphasis on real-world deployment, robustness, and scalability.
You will collaborate closely with Perception, Navigation, Controls, Reinforcement Learning, and Platform teams, and help shape Apptronik’s long-term autonomy strategy.
ESSENTIAL DUTIES AND RESPONSIBILITIES or KEY ACCOUNTABILITIES
- Design and implement mission-level autonomy systems for humanoid robots, focusing on learning-based decision making and behavior execution.
- Develop policy execution, monitoring, and coordination layers that integrate learning-based components with classical robot subsystems.
- Build autonomy frameworks that support adaptive behavior, generalization across tasks, and robustness to uncertainty and environmental variation.
- Implement recovery, fallback, and safety mechanisms around learning-based autonomy to ensure reliable real-world operation.
- Define and maintain clean interfaces between autonomy, perception, navigation, manipulation, and control systems.
- Collaborate with Reinforcement Learning teams to integrate trained policies into real-time robot software stacks.
- Develop infrastructure for telemetry, logging, evaluation, and replay to understand and debug autonomy behavior.
- Validate autonomy systems in simulation and on physical humanoid robots, closing the loop from research to deployment.
- Contribute to autonomy architecture, code quality, CI/CD pipelines, and long-term maintainability.
- Mentor junior engineers and provide technical leadership within the autonomy organizatio