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Internship German Machine Learning information

What is an internship German machine learning?

An Internship German Machine Learning is a temporary training position typically offered by companies or research institutions in Germany, focusing on practical experience in machine learning. Interns work on real-world projects involving data analysis, algorithm development, and model implementation under supervision. These internships help students or recent graduates gain hands-on skills, industry exposure, and networking opportunities in the rapidly growing field of artificial intelligence and machine learning.

What is the difference between Internship German Machine Learning vs Data Scientist German?

AspectInternship German Machine LearningData Scientist German
Required CredentialsBasic programming, coursework in MLAdvanced degree in data science, statistics, or related
Work EnvironmentInternship setting, learning-focusedFull-time, project-driven
Industry UsageEntry-level roles, training programsProfessional roles, decision-making

Internship German Machine Learning positions are typically entry-level, focusing on learning and skill development, often requiring basic programming and coursework. Data Scientist German roles are more advanced, requiring higher education and experience, with responsibilities in analyzing data and building models. The internship provides a stepping stone into the data science field, while the data scientist role involves applying expertise to solve complex problems.

What types of projects can I expect to work on during a German machine learning internship?

As a German Machine Learning intern, you'll typically assist with real-world projects such as developing and testing machine learning models, preprocessing datasets, and supporting the implementation of AI solutions in both German and international contexts. You may also help with data analysis, model evaluation, and documentation, often collaborating with data scientists and engineers. These projects provide hands-on experience with industry-standard tools and workflows, helping you build practical skills and a strong professional network.

What are the key skills and qualifications needed to thrive as an internship German machine learning?

To thrive as an Internship German Machine Learning, you need a solid understanding of machine learning concepts, programming skills in Python, and progress toward a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, and data analysis libraries, as well as experience using version control systems like Git, is typically required. Strong analytical thinking, problem-solving ability, and effective communication—especially in both English and German—help you collaborate within diverse teams. These skills and qualifications are essential for successfully contributing to machine learning projects and adapting to the fast-evolving tech industry.
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Internship German Machine Learning jobs near you

Research Engineer - Machine Learning & Robotics

Jumio Corporation

Lenexa, KS • On-site

Full-time

Re-posted 11 days ago

Job description

Job Summary:
Jumio Corporation is a B2B technology company dedicated to eradicating online identity fraud and financial crimes. They are seeking a Research Engineer to help build and scale systems for data collection, model development, and product improvement in the fields of machine learning and robotics.
Responsibilities:
• Build and integrate ROS/ROS2-based modules to support robotic navigation, manipulation, and data collection workflows.
• Replicate and integrate mobile and web UI environments into robotic testing and data collection systems.
• Build, maintain, and improve training and test datasets collected through robotic manipulators and in-house iOS and Android applications.
• Mine, query, and analyze data from internal databases to create features, identify trends, and generate insights that improve product and model development.
• Develop tools and processes to monitor data quality, model performance, and model accuracy in production environments.
• Implement end-to-end machine learning workflows, including data preparation, model training, testing, evaluation, and deployment support.
• Write clean, modular, well-documented C++ and Python code that can be maintained and extended by other engineers.
• Collaborate cross-functionally with machine learning, engineering, product, and research teams to improve data collection, model development, and system performance.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field.
• 1–2 years of relevant industry, internship, or research experience in machine learning, robotics, computer vision, or related technical areas.
• Hands-on experience with ROS and/or ROS2, including building or integrating modules for robot navigation, manipulation, simulation, or data collection.
• Strong foundation in machine learning fundamentals, with experience implementing models in Python using frameworks such as PyTorch, TensorFlow, scikit-learn, or similar.
• Experience working with databases, writing queries, and building or maintaining data pipelines for training, testing, or evaluation.
• Strong programming skills in Python and C++, with an emphasis on clean, reliable, well-documented code.
• Ability to work hands-on with physical hardware, debug system behavior, and translate research or prototype work into scalable engineering solutions.
Preferred:
• Experience with robotic manipulators, mobile robot platforms, or lab-based robotic systems.
• Familiarity with iOS and/or Android development, especially for hardware-integrated data collection applications.
• Experience with data collection pipelines for computer vision, biometric systems, identity verification, or similar applied AI domains.
• Exposure to production ML observability, model monitoring, drift detection, or data quality monitoring tools.
• Familiarity with cloud platforms such as AWS, including S3, EC2, SageMaker, or similar tools for storage, compute, and model deployment.
• Experience working in cross-functional environments with machine learning engineers, software engineers, researchers, and product teams.
Company:
Jumio helps organizations to know and trust their customers online. Founded in 2010, the company is headquartered in Sunnyvale, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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