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Reinforcement Learning Engineer at Apptronik - ApplyBlast

Reinforcement Learning Engineer

Apptronik

2 months ago

4.0 on Glassdoor

Austin, Texas, United States

Onsite

Full Time

Senior

0 applicants

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About this role

The Reinforcement Learning Engineer will design advanced neural network architectures and implement state-of-the-art RL algorithms to enable whole-body locomotion and manipulation on humanoid robots. Working closely with hardware and controls teams, the role involves developing high‑performance policies, optimizing training pipelines, and transferring solutions from simulation to physical hardware. The engineer will also contribute to a collaborative, high‑velocity engineering culture through code reviews and knowledge sharing.

Responsibilities

Implement and deploy state-of-the-art RL algorithms on physical hardware
Drive development from simulation prototyping to robot policy transfer
Optimize and scale RL training pipelines for high‑throughput simulation

Skills

Qualifications

PhD in Computer Science, Robotics or related fieldMS in Computer Science, Robotics or related field

About Apptronik

apptronik.com

Headquarters

Austin, Texas, United States

Company Size

51-200 employees

Founded

2015

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Apptronik is a robotics company that develops Apollo, an AI-powered humanoid robot designed to perform physically demanding, repetitive, and hazardous work in environments built for humans. Apollo features advanced mobility (bipedal and wheeled), dexterous manipulation, and the ability to learn new skills, serving industries including manufacturing, warehousing, logistics, and retail. Apptronik combines custom hardware, embodied AI, and fleet-level software to deliver a scalable humanoid robotics platform with a human-centered design philosophy.