Senior AI Engineer - Reinforcement Learning at Apptronik

Austin, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Dec, 25

Salary

0.0

Posted On

26 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Reinforcement Learning, Python, C++, Robotics, Simulation, Distributed Training, Imitation Learning, Model-Based RL, Sim-To-Real Transfer, Robot Dynamics, Controls Theory, Technical Guidance, Code Reviews, Mentoring, Algorithm Development, Hardware Integration

Industry

Robot Manufacturing

Description

Apptronik is building robots for the real world to improve human quality of life and to help solve the ever-increasing labor shortage problem. Our team has been building some of the most advanced robots on the planet for years, dating back to the DARPA Robotics Challenge. We apply our expertise across the full robotics stack to some of the most important and impactful problems our society faces, and expect our products and technology to change the world for the better. We value passion, creativity, and collaboration to help us overcome existing technological barriers in the industry to create truly innovative products. You will join a team developing state-of-the-art general-purpose robots designed to operate in human spaces and with human tools. It is designed to work alongside humans, mobilize to human spaces, and manipulate the world around it. JOB SUMMARY: The Senior AI Engineer - Reinforcement Learning is a key, hands-on role focused on achieving state-of-the-art performance on our humanoid robots. This engineer will leverage their deep expertise in RL to solve critical locomotion and manipulation challenges and deliver breakthrough results on physical hardware. The primary focus of this role is to rapidly implement, iterate, and deploy advanced learning algorithms to push the boundaries of what our robots can do. As a senior member of the team, this individual will also be responsible for mentoring junior engineers, elevating the team's overall technical capabilities through their guidance and expertise. ESSENTIAL DUTIES AND RESPONSIBILITIES or KEY ACCOUNTABILITIES: Implement and deploy state-of-the-art RL algorithms to achieve ambitious, world-class performance on dynamic locomotion and manipulation tasks with physical hardware. Drive the entire development cycle, from prototyping in simulation to robustly transferring and fine-tuning policies on the robot. Optimize and scale the RL training pipeline for faster iteration, contributing to core infrastructure for high-throughput simulation and distributed training. Mentor junior engineers by providing technical guidance, conducting insightful code reviews, and sharing best practices in reinforcement learning and software development. Collaborate closely with the robotics and hardware teams to diagnose system-level issues and co-develop solutions that enable more complex learned behaviors. Analyze and present hardware results to guide future technical directions and demonstrate progress on key company objectives. SKILLS AND REQUIREMENTS Deep, hands-on expertise (5+ years) with common RL frameworks (e.g., PyTorch, JAX) and high-fidelity physics simulators (e.g., MuJoCo, IsaacGym) Mastery of Python for rapid prototyping and training, alongside strong proficiency in C++ for developing performant, deployable code. Experience building or utilizing large-scale, distributed training pipelines and a strong intuition for their optimization. A strong theoretical understanding of modern reinforcement learning, including deep expertise in areas like imitation learning, model-based RL, and sim-to-real transfer techniques. A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches. A results-oriented mindset with a passion for seeing complex algorithms work on real-world hardware. EDUCATION and/or EXPERIENCE: A PhD or MS in Computer Science, Robotics, or a related field, with 2+ years industry experience strongly preferred. A proven track record of successfully deploying learning-based policies on physical robotic systems, especially legged robots or manipulators. Demonstrated experience mentoring or providing technical guidance to other engineers in a team environment. A strong publication record in relevant conferences or journals (e.g., CoRL, RSS, ICRA) is a significant plus. 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.

Responsibilities

The Senior AI Engineer - Reinforcement Learning will implement and deploy advanced RL algorithms to enhance the performance of humanoid robots. This role involves driving the development cycle from simulation to real-world application and mentoring junior engineers.