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Internship German Machine Learning Jobs in Wisconsin

... Betrieb skalierbarer Machine-Learning- und LLM-Losungen auf Azure Databricks von der ... Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ...

Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ... Microsoft Foundry, Azure Cognitive Services, Azure Machine Learning Erfahrung in der Entwicklung ...

Turf - Student Intern

Hartford, WI · On-site

$16.25 - $21.75/hr

Student Interns will be required to: * Work extended hours, which includes weekend and holiday shifts * Work outside in all weather conditions * Work on or near heavy machinery * Stand for extended ...

Turf - Student Intern

Hartford, WI · On-site

$16.25 - $21.75/hr

Student Interns will be required to: * Work extended hours, which includes weekend and holiday shifts * Work outside in all weather conditions * Work on or near heavy machinery * Stand for extended ...

This position will utilize data and develop reports, while also being dedicated to learning the ... Demonstrate acceptance and training of student interns in the department, as directed. Participate ...

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Internship German Machine Learning information

Which 3 jobs will survive AI?

Jobs that require complex human skills such as machine learning engineers, data scientists, and cybersecurity specialists are likely to persist as AI automates routine tasks. These roles demand critical thinking, creativity, and specialized knowledge that are difficult for AI to replicate fully. Continuous learning and expertise in AI tools can enhance job security in these fields.

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.

Can foreigners intern in Germany?

Foreigners can intern in Germany if they meet visa and work authorization requirements, which vary depending on their nationality and the internship duration. Internships often require a valid visa or residence permit, especially for non-EU/EEA citizens, and may need to comply with labor laws and internship regulations. It is important to check specific visa conditions and employer sponsorship options before applying.

How much do ML interns get paid?

Machine Learning interns typically earn between $15 and $30 per hour, depending on the company, location, and level of experience. Paid internships often include opportunities to work with tools like Python, TensorFlow, or PyTorch and may be full-time or part-time during the summer or semester.

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, and why are they important?

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.

Is AI in demand?

AI skills are highly in demand for machine learning internships, including roles focused on developing and applying artificial intelligence technologies. Companies seek candidates with knowledge of programming languages like Python, experience with frameworks such as TensorFlow or PyTorch, and understanding of data analysis. The AI industry continues to grow, creating numerous opportunities for interns with relevant skills and training.
What are popular job titles related to Internship German Machine Learning jobs in Wisconsin? For Internship German Machine Learning jobs in Wisconsin, the most frequently searched job titles are:
What cities in Wisconsin are hiring for Internship German Machine Learning jobs? Cities in Wisconsin with the most Internship German Machine Learning job openings:

Databricks AI / ML Engineer (m/w/d)

Qualysoft

On-site, Remote

Contractor

Re-posted 15 days ago


Job description

Fur ein langfristig angelegtes Daten- und KI-Programm wird ein Databricks AI / ML Engineer (m/w/d) gesucht.
Ziel ist die Entwicklung, Implementierung und der Betrieb skalierbarer Machine-Learning- und LLM-Losungen auf Azure Databricks von der Datenaufbereitung uber Feature Engineering bis hin zu MLOps, Deployment und Monitoring.
Der Fokus liegt auf Big-Data-Engineering, ML/LLM-Workloads, MLOps-Automatisierung sowie der nahtlosen Integration in das Microsoft-Okosystem.
520 - 560 a day
Rahmenbedingungen
Start: Marz/April 2026
Laufzeit: 3 Jahre (optional verlangerbar bis max. 5 Jahre)
Auslastung: 100 %
Arbeitsmodell: Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote
Projektsprache: Deutsch und Englisch

Aufgaben:
Datenanalyse und Prototyping mit Python in Azure Databricks unter Einsatz gangiger ML-Frameworks
Entwicklung und Betrieb von Big-Data-Pipelines mit Apache Spark, Delta Lake und Databricks SQL
Durchfuhrung von Feature Engineering sowie Training, Versionierung und Deployment von Modellen mit Databricks MLflow
Entwicklung und Betrieb von ML- und LLM-Workloads auf Azure Databricks (inkl. Unity Catalog, Performance- und Kostenoptimierung)
End-to-End-Integration der Losungen in das Microsoft-Okosystem (z. B. API- und Schnittstellendesign, Orchestrierung mit Azure Functions und Logic Apps)
Aufbau und Weiterentwicklung von MLOps- und CI/CD-Pipelines fur automatisiertes Training, Testing, Deployment und Monitoring von ML- und LLM-Modellen sowie Agents
Durchfuhrung von Modell- und Datenmonitoring (Modellleistung, Daten-Drift, Bias) inklusive Wartungs- und Updateprozessen
Einsatz von AutoML-Tools zur Beschleunigung von Prototypen und Experimenten
Sicherstellung von Skalierbarkeit, Sicherheit und stabilen Betriebsprozessen der entwickelten Losungen

Fachliche Anforderungen:
Fundierte Kenntnisse in Datenanalyse und Prototyping mit Python in Azure Databricks
Erfahrung mit Machine-Learning-Frameworks wie TensorFlow, PyTorch und scikit-learn
Praktische Erfahrung im Big Data Engineering mit Apache Spark, Delta Lake und Databricks SQL
Kompetenz in Feature Engineering sowie Modell-Deployment mit managed Databricks MLflow
Erfahrung in der Entwicklung und dem Betrieb von ML- und LLM-Workloads auf Azure Databricks
Erfahrung mit End-to-End-Integrationen im Microsoft-Okosystem
Erfahrung im Aufbau von MLOps- und CI/CD-Pipelines fur ML- und LLM-Modelle sowie agentische Workflows
Erfahrung im Modell- und Datenmonitoring (Leistung, Drift, Bias) inklusive passender Wartungsstrategien
Praktische Erfahrung im Einsatz von AutoML-Tools
Vorhandensein einer eigenen, vom Produktivsystem des Auftraggebers getrennten Entwicklungsumgebung, die den aktuellen Standards fur Datensicherheit und Zugriffsschutz entspricht (inkl. Nachweis der Infrastruktur)

PLUS:
Erfahrung mit Data- und KI-Governance
Erfahrung in der Konzeption und Umsetzung agentischer Ansatze (Agenten, Multi-Agent-Systeme, agentische Workflows) mit Azure-Ressourcen
Erfahrung in der Umsetzung von End-to-End-Databricks-Projekten (von Datenaufbereitung und Feature Engineering uber Modelltraining und Deployment bis zu MLOps und Monitoring)
Branchenkenntnisse in der Energieindustrie
Strukturierte und analytische Arbeitsweise
Hohes Qualitatsbewusstsein und Verantwortungsbereitschaft
Sehr gute Kommunikationsfahigkeit gegenuber technischen und fachlichen Stakeholdern
Teamfahigkeit und Bereitschaft zur Wissensweitergabe

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