Staff Software Engineer - Humanoid Controls

Apptronik • Austin, TX

5d • Onsite

About The Position

Apptronik is building robots for the real world — to improve human quality of life and help solve the ever-increasing labor shortage. As a Staff Software Engineer – Humanoid Controls, you will be a senior technical force multiplier on our Motion Control & Planning team — the person who raises the quality of our robotics stack and moves to wherever the hardest problem is. Your scope spans whole-body control for our wheeled-base platform and our biped, learning-based hand control, mobile manipulation, and teleoperation — translating state-of-the-art controls and learning into real capability while setting technical direction for the team.

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