Staff Software Engineer - Humanoid Controls

Apptronik • Austin, TX

6d • Onsite

About The Position

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 Applied 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.

Requirements

• Deep robotics fundamentals: kinematics, dynamics, state estimation, and optimization/control theory.
• Proven expertise in whole-body control (WBC/OSC, QP-based control, or MPC) for floating-base (legged) or mobile (wheeled) systems.
• Hands-on experience with learning-based control / reinforcement learning applied to robotics (training in simulation).
• Breadth across robot control problems — mobile manipulation, dexterity / hand control, and teleoperation — and the versatility to move between them.
• Strong software engineering: real-time C++ and Python for robotic systems.
• Industry experience developing production-grade controllers, including hands-on experience validating or deploying algorithms on physical robot hardware.

Nice To Haves

• Shipping controllers to a production fleet or to market at scale
• Dexterous / in-hand manipulation
• Legged locomotion
• Safety-critical / certified software (ISO 13849, 10218, IEC 61508)

Responsibilities

• Raise the quality of the overall controls stack — architecture, algorithms, real-time performance, testing, and long-term maintainability.
• Advance whole-body control across our platforms — the wheeled-base robot and the biped — coordinating the base or legs with upper-body manipulation.
• Flex across the stack to the highest-impact problems — e.g. learning-based hand control (RL in simulation), mobile manipulation, teleoperation, and estimation.
• Translate state-of-the-art model-based and learning-based methods into robust capability, from simulation through hardware bring-up and deployment.
• Expand the robot's performance envelope — speed, payload, reliability, and safety — with measurable, defensible improvements.
• Set technical direction across the controls stack, influencing the roadmap and bringing adjacent teams (locomotion, manipulation, teleoperation, RL, estimation) along.
• Mentor engineers and multiply team capability through design reviews, code reviews, and best practices.
• Collaborate cross-functionally with hardware, systems, and RL teams to co-develop solutions and diagnose system-level issues.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior