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.

Core Responsibilities

• 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 organization.

Required Qualifications

• MS, or PhD in Robotics, Computer Science, Computer Engineering, or a related field.
• 2+ years of experience developing robot autonomy or learning-based robotic systems.
• Strong proficiency in modern C++ and working knowledge of Python in Linux environments.
• Experience integrating learning-based policies (e.g., reinforcement learning, imitation learning, foundation-model-based policies) into real robot systems.
• Solid understanding of robotics systems, including:
• State representation and estimation interfaces
• Interaction between autonomy, perception, navigation, and control
• Real-time and distributed software systems
• Experience deploying autonomy software on physical robots, including debugging and tuning under real-world constraints.
• Familiarity with ROS 2, message-passing architectures, and modular robot software design.
• Strong software engineering fundamentals: testing, CI/CD, code reviews, documentation, and system reliability.

Preferred Qualifications

• Experience with humanoid robots, mobile manipulators, or legged robotic systems.
• Hands-on experience with reinforcement learning or learning-based control for robotics.
• Familiarity with foundation models for robotics (e.g., vision-language-action models, multimodal policies).
• Experience designing safe wrappers, monitors, or supervisors around learning-based systems.
• Contributions to open-source robotics, autonomy, or ML infrastructure.
• Experience working in fast-paced robotics startups or deploying systems into production.