Motion Control and Planning Intern
Company: Apptronik
Location: Austin
Posted on: April 1, 2026
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Job Description:
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
Reinforcement Learning Intern, you will be at the forefront of
making humanoid robotics a reality. This is a hands-on role where
you will work directly with a senior mentor to plan, develop, and
execute a high-impact project that showcases new functionality on
our physical robot systems. You will bridge the gap between
simulation and reality, gaining deep technical exposure to
hardware, software, and project management in a fast-paced,
collaborative environment. ESSENTIAL DUTIES AND RESPONSIBILITIES or
KEY ACCOUNTABILITIES: Project Ownership: Partner with a mentor to
define and execute a scoped RL project—from initial simulation to
deploying a functional demo on humanoid hardware. Sim-to-Real
Development: Iterate on learning algorithms in high-fidelity
simulators and assist in the "sim-to-real" transfer process to
ensure robust performance on physical robots. Collaborative
Engineering: Work alongside our robotics and hardware teams to
troubleshoot system-level challenges and understand the interplay
between code and motors. Pipeline Optimization: Help refine
training pipelines or data processing tools (such as motion
retargeting from human demonstrations) to improve how our robots
learn. Technical Communication: Present your project findings and
hardware results to the broader engineering team, gaining
experience in how to translate data into technical milestones.
SKILLS AND REQUIREMENTS Foundational Knowledge: A strong
theoretical understanding of Reinforcement Learning (RL) and robot
dynamics. Technical Stack: Proficiency in Python and experience
with common RL frameworks (e.g., PyTorch, JAX ). Simulation Tools:
Familiarity with physics simulators such as MuJoCo, IsaacGym, or
Drake . Coding Standards: Ability to write clean, maintainable
code; exposure to C++ is a significant plus. Problem-Solving
Mindset: A "hacker" mentality—you are excited to get your hands
dirty, troubleshoot hardware glitches, and see your code move a
physical system. Collaboration: Excellent communication skills and
a desire to learn from a world-class team of engineers. EDUCATION
and/or EXPERIENCE: Currently enrolled in a BS , MS, or PhD program
in Robotics, Computer Science, Mechanical Engineering, or a related
technical field. Prior experience (academic or personal projects)
involving robotic control or machine learning. Experience with
legged robots or robotic manipulators is a plus but not required.
PHYSICAL REQUIREMENTS: Prolonged periods of sitting at a desk and
working on a computer Vision to read printed materials and a
computer screen Hearing and speech to communicate *This is a direct
hire. Please, no outside Agency solicitations. Apptronik provides
equal employment opportunities to all employees and applicants for
employment and prohibits discrimination and harassment of any type
without regard to race, color, religion, age, sex, national origin,
disability status, genetics, protected veteran status, sexual
orientation, gender identity or expression, or any other
characteristic protected by federal, state or local laws.
Keywords: Apptronik, Austin , Motion Control and Planning Intern, IT / Software / Systems , Austin, Texas
