Rivr18mo ago

Reinforcement Learning Intern

ZürichInternshipentry

OtherIntern

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pythonpytorchtensorflowdeep-learning

RIVR is a Swiss robotics company pioneering Physical AI and robotic solutions to revolutionize last-mile delivery, giving 1 human the power of 1000. Through the combination of artificial neural networks and innovative robot designs with wheels and legs, RIVR aims to enhance efficiency, sustainability, and scalability in last-mile delivery. Founded as Swiss-Mile, the company rebranded to RIVR in 2025 to better reflect its mission of driving the future of intelligent robotics.

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.

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

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.

Proven experience implementing reinforcement learning algorithms.

Familiarity with modern simulation frameworks for reinforcement learning, such as IsaacSim.