Reinforcement Learning Intern

Swiss-Mile Robotics AG is a deep-tech startup that connects AI with the physical world through autonomous wheeled-legged robots. These robots are designed to revolutionize monitoring, security, logistics applications, and beyond. Backed by leading global venture capitalists, we are on a mission to enhance our team with world-class talent. Join our innovative team, renowned for pioneering robotic design and neural network applications in robotics that improve environmental understanding and decision-making. With a robust research foundation and notable contributions from ETH Zurich, we are leaders in translating artificial intelligence and robotics into practical, real-world applications.
As a Reinforcement Learning Intern, you will assist the AI engineering team in developing and implementing reinforcement learning algorithms for robotic systems. Additionally, your responsibilities include extending the software stack to evaluate our algorithms in simulation and on hardware. This role offers hands-on experience in algorithm development, software integration, and testing within a dynamic and collaborative environment. We are committed to finding and nurturing exceptional talent; our internships are a key pathway to recruiting outstanding graduates who can make a significant impact in our team.
Important Notice: For this position, we can unfortunately only accept applications from citizens of Schengen Area countries. This restriction does not apply to ETHZ and EPFL students who are required to complete compulsory internships as part of their studies.

What you’ll be doing

• Support the team in developing, debugging, and testing reinforcement learning algorithms for robotic applications.
• Work closely with senior engineers to integrate software with hardware components and contribute ideas to enhance system performance.
• Engage in continuous learning and gain exposure to recent developments from the reinforcement learning literature

What you must have

• At least BSc in Robotics, Engineering, Computer Science or equivalent.
• Previous coursework or projects related to reinforcement learning or learning-based control.
• Proficiency in Python and at least one common deep learning framework, such as PyTorch, Jax or TensorFlow.
• Eagerness to learn and contribute in a team environment.
• Strong problem-solving and analytical skills.

Get some bonus points

• Proven experience implementing reinforcement learning algorithms.
• Familiarity with modern simulation frameworks for reinforcement learning, such as IsaacSim.

We are looking forward to receive your application.