Intern (m/f/d) Robot Learning

The AI Teams at Agile Robots are looking for an Intern (m/f/d) Robot Learning , who will help train and evaluate machine-learning models for real robots during a six-month student internship .

This posting is for our intern talent pool and serves as an entry point to several of our AI teams . We review applications on a rolling basis and contact you when an internship matching your profile becomes available, typically several months before its start date. We match you with a team and a project during the interview process, and your exact responsibilities depend on that match .

Possible Responsibilities

Agentic Planning: Build and test systems that use language or vision-language models to plan, sequence, and monitor robot tasks over multiple steps.

Sim-to-Real Transfer: Apply domain randomization and realism modeling to reduce the gap between simulated and real sensor and actuator data.

Model Training: Train, fine-tune, or adapt machine-learning models for robot perception, manipulation, or task planning, including adapting an existing model to a specific robot and task.

Model Evaluation: Design and run experiments in simulation and on real robots to measure where a model works and where it fails, and trace failures to the data, the model, or the setup.

Data Preparation: Collect, clean, and annotate robot data, including teleoperation demonstrations and experiment records from real hardware.

Essential Skills

Degree Programme: Enrolled in a Master’s programme in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field.

Machine Learning: Hands-on experience training and evaluating neural networks in PyTorch or a comparable framework, gained through coursework, projects, or research.

Project Experience: At least one machine-learning project in which you prepared the data and designed the evaluation yourself.

Python Programming: Working proficiency in Python for machine-learning and robotics development.

Robot Simulation: Working familiarity with at least one physics simulator, such as MuJoCo, Isaac Sim, or Gazebo.

Beneficial Skills

Language Agents: Experience building a system in which a language or vision-language model plans or triggers actions in a simulator or on a robot.

Robot Learning: Experience with imitation learning, reinforcement learning, or vision-language-action models.

Sensor Modeling: Exposure to sensor noise models, actuator dynamics, or domain randomization techniques.

Robot Hardware: Experience running code on a physical robot or sensor setup, for example in a university lab or a student robotics team.

ROS 2: Familiarity with ROS 2 and how robot software components communicate.

What we offer

A dynamic high-tech company, combined with financial soundness and world-class investors.

Join an interdisciplinary, international team with 60+ different nationalities in a collaborative work environment.

Lots of development opportunities as we continue to grow.

Challenging tasks and impactful projects alongside experts that enable professional and personal growth.

Corporate Benefits Program covering health, mobility, and learning for 100€ net per month.

Modern office facilities with a rooftop terrace overlooking Munich, free drinks & fruits, and regular company events contribute to a good working environment

About us

Agile Robots is a leading provider of AI-powered robotics solutions. By combining artificial intelligence and robotics, the company makes industries smarter, more flexible, and more efficient.

Founded in Munich in 2018 by renowned robotics researchers from the German Aerospace Center (DLR), Agile Robots has experienced rapid global growth. Today, more than 3,500 highly skilled robotics and AI enthusiasts are employed worldwide. The company has one of the largest research and development teams in the AI and robotics industry.

Agile Robots has built a unique portfolio, together with the subsidiaries BÄR Automation, Franka Robotics, idealworks, and Krause Automation, the company covers all areas of AI-driven robotics.

Find out more at: https://www.agile-robots.com/en/