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Stuttgart, Baden-Württemberg, Deutschland
Hybrid
We build the intelligence that lets robots sense, reason, and act in the real world—moving beyond the lab and into everyday industrial settings like warehouses and factories. Our technology closes the automation gaps that traditional systems can't solve. We are on a mission to redefine how physical work gets done, and we're looking for curious, bold thinkers to help shape the future of robotics with us.
We are looking for a curious and detail-oriented intern to join our data and machine learning team. In this role, you will work alongside our ML and engineering teams to help prepare, label, and analyze data that powers our robotic perception and decision-making systems. This is an excellent opportunity to get hands-on experience with real-world ML pipelines in an AI robotics startup.
Perform data labeling and annotation activities for training and evaluating machine learning models.
Help maintain and improve annotation quality standards and guidelines.
Work with various data types including images, point clouds, and sensor data from robotic systems.
Assist with data analysis, cleaning, and preparation for model training and evaluation.
Help build and maintain data pipelines and tooling to streamline data workflows.
Generate reports and visualizations to enable data-driven decision-making.
Contribute to model training, evaluation, and related ML activities.
Help track and document experiment results, model performance metrics, and dataset versions.
Assist with integrating trained models into the product pipeline for testing and validation.
Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Engineering, or a related technical field.
Coursework or project experience in machine learning, data science, or computer vision is a plus.
Proficiency in Python programming.
Basic understanding of machine learning concepts (supervised learning, model training and evaluation).
Experience with data manipulation libraries such as NumPy, Pandas, or similar.
Familiarity with data visualization tools (Matplotlib, Seaborn, or similar).
Strong attention to detail and a structured approach to working with data.
Good communication skills and the ability to work collaboratively in a team.
Experience with computer vision libraries (OpenCV, torchvision) or deep learning frameworks (PyTorch, TensorFlow).
Familiarity with annotation tools (e.g., Label Studio, CVAT, or similar).
Experience working with Docker or cloud-based ML environments.
Knowledge of German is a plus.
Recruiter screen: A conversation to learn about your background, interests, and availability.
Technical screen: A deeper look into your skills, problem-solving approach, and technical fit for this role.
Final round: Meet the team leadership, discuss the role in more detail, and get a clear feel for the working environment.
Wellpass (gym membership)
Flexible working hours
Option to work from home when needed
A motivated team and an open corporate culture
Hands-on experience with cutting-edge AI robotics technology
Mentorship and learning opportunities within a fast-paced startup
