Robotics ML and Data Intern

Sereact GmbH·Stuttgart Schockenriedstr. 17junior

En corto

→Trabajar en desarrollo de inteligencia artificial para robots industriales, etiquetando datos y mejorando pipelines.
→Día a día: etiquetado de imágenes y puntos, análisis de datos, apoyo en entrenamiento de modelos con Python y herramientas ML.
→Lo destacado: experiencia real en IA robótica de vanguardia en una startup con impacto en fábricas y almacenes.

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

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¿Qué piden?

✓Estudiante o recién graduado en Ciencia de Datos, Informática, Ingeniería o campo técnico relacionado.
✓Dominio de Python y herramientas como NumPy, Pandas.
✓Conocimiento básico de aprendizaje automático (entrenamiento, evaluación de modelos).
✓Atención al detalle y enfoque estructurado con los datos.
✓Capacidad para trabajar en equipo y comunicar ideas claramente.
✓Experiencia previa o proyecto en visión por computadora, ML o análisis de datos.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

PythonNumPyPandasMatplotlibSeabornOpenCVtorchvisionPyTorchTensorFlowLabel Studio

¿A quién escribirle en Sereact GmbH?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

Who We Are 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. Overview 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. Responsibilities Data Labeling & Annotation 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. Data Analysis & Preparation 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. ML Activities 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. Qualifications Education and Experience 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. Skills 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. Additional Skills / Nice to Have Experience with computer vision libraries (OpenCV, torchvision) or deep learning frameworks (PyTorch, TensorFlow). , Label Studio, CVAT, or similar). Experience working with Docker or cloud-based ML environments. Knowledge of German is a plus. Our Interview Plan 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.

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