A

Data Science Intern

ai superior • Germany
Remote
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AI Summary

Join AI Superior as a Data Science Intern to contribute to real client projects, gain experience in AI and Machine Learning, and establish yourself as an expert in the field.

Key Highlights
Work on AI-/ML-projects with a focus on LLM-related processes
Support the development and testing of machine learning pipelines
Contribute to data cleaning, annotation, and preprocessing tasks
Key Responsibilities
Work on AI-/ML-projects with a focus on LLM-related processes
Support the development and testing of machine learning pipelines
Contribute to data cleaning, annotation, and preprocessing tasks
Technical Skills Required
Python Machine Learning
Benefits & Perks
Paid internship
Full-time remote position
Flexible working hours
Nice to Have
Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, or Hugging Face Transformers
Experience with fine-tuning or evaluating language models
Knowledge of vector databases and embedding-based retrieval

Job Description


AI Superior is an AI agency founded in 2019, providing AI development and consulting long before the recent hype. Our clients range from startups and NGOs to international corporations such as Boehringer Ingelheim, Siemens, or the European Space Agency. We support them from proof of concept all the way to production, across Data Science, Machine Learning, and AI consulting.


While we are originally based in Germany, we have a presence across Europe. Being fully remote, we offer flat hierarchies, high flexibility, and a team that genuinely cares about pushing the state of the art.


We are looking for a motivated Data Science Intern (full-time, remote) to join our team and contribute to real client projects from day one. You will work across general Machine Learning and AI topics, with a particular focus on Large Language Models (LLMs): This is a great opportunity to get into the domain of AI, gain real experience on projects and establish yourself as an expert in the field.


Responsibilities

  • Work on AI-/ML-projects with a focus on LLM-related processes: prompt engineering, fine-tuning, retrieval-augmented generation (RAG), evaluation, etc.
  • Support the development and testing of machine learning pipelines, from data processing to deployment
  • Contribute to data cleaning, annotation, and preprocessing tasks
  • Assist in building internal tools, packages, and reusable components
  • Prepare presentations, technical summaries, and analytical materials
  • Stay current with state-of-the-art LLM research and assess applicability to client use cases


Qualifications

  • Current student or recent graduate in a Master's or Ph.D. program in Computer Science, Mathematics, Statistics, or a related quantitative field
  • Solid Python skills and familiarity with common data science libraries (NumPy, pandas, scikit-learn, matplotlib)
  • Deep understanding of Machine Learning fundamentals (classification, regression, validation, feature engineering, etc.)
  • Familiarity with LLMs and transformer-based models (e.g., GPT, LLaMA, Mistral), whether through coursework, projects, or self-study
  • Fluent in German (spoken and written) and proficient in English


Nice-to-Haves

  • Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, or Hugging Face Transformers
  • Experience with fine-tuning or evaluating language models
  • Knowledge of vector databases and embedding-based retrieval
  • Basic software development practices: OOP, version control (Git), and CI/CD
  • Experience with cloud platforms (AWS, GCP, or Azure)
  • Active GitHub profile, Kaggle participation, or published work
  • German language skills are a plus, but not a requirement :)


Conditions

  • Paid internship
  • Full-time remote position (please make sure this is in line with your university's expecations)
  • 6-month minimum duration
  • Flexible working hours
  • Direct exposure to real client projects that go to production
  • Mentoring by experienced Data Scientists and ML Engineers
  • Start-up environment with flat hierarchies and room to grow


Any questions do not hesitate to reach out :)


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