Gravis Robotics
Reinforcement Learning Engineer Internship
Job Description
About the JobWe are looking for passionate, skilled interns to join our team—and to actively contribute to the development and deployment of extraordinary construction robots. The ideal candidate should be self-motivated, capable of working autonomously and in small teams, and should have a strong desire to solve exciting, challenging, and applied problems.At Gravis, we engineer solutions at the nexus of hardware and software every day.
List of possible opportunities
- Contribute to ongoing customer projects
- Improve reinforcement learning training framework
- Investigate improvements to learning policies
- Train, validate and deploy trained policies
- Explore techniques expanding our training environment
Requirements
- Currently pursuing a degree at a Swiss university
- Experience with Python
- Understanding of deep reinforcement learning
Beneficial
- Enrolled in Master’s level study (i.e. in robotics, computer science, aerospace, mechanical or electrical engineering, design)
- Experience conducting research (e.g., through experience in an academic lab, or through previous internships and employment)
- Experience with training and deployment of RL policies
- Experience working with real hardware
- Motivation to test policies on the real excavator
- Experience with simulation software such as Gazebo, Isaac Gym, Isaac Sim, etc.
- Proficiency with Linux, GIT, and ROS/ROS2
- Interest and/or experience in heavy construction
This is an opportunity to join a dynamic and versatile team, and to be part of a young startup that will revolutionize heavy construction. You will get the chance to apply your skills to critical tasks, while learning from a team of world-class robotic engineers. Gravis Robotics offers a fair market salary and an excellent working location in the heart of Zurich.
Gravis is an equal opportunity employer. We are committed to inclusion and diversity, and do not discriminate based upon race, color, ancestry, national origin, religion, sex, sexual orientation, age, gender identity, gender expression, disability, veteran status, or other legally protected characteristics. All qualified people are highly encouraged to apply.