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Working Student Machine Learning (all genders)

Avelios Medicalvor 2 MonatenAktualisiert vor 2 TagenWerkstudent
Vor OrtEnglisch erforderlichDeutsch von Vorteil (nicht erforderlich)TechKI, ML & Data Science

Erforderliche Skills

ASRHuggingFaceLLMsQdrantFederated LearningPyTorchPydanticVector DatabasesLangChainRAGPythonGitHub

Stellenbeschreibung

Avelios Medical hat diese Stelle ausgeschrieben. Unten erklären wir, was sie für dich als Werkstudent:in in Munich bedeutet: deine Wochenstunden, dein Netto und deine Visumsgrenzen. Du kannst außerdem ChatGPT oder Claude mit einem fertigen Prompt öffnen, um deinen Lebenslauf anzupassen, deine Eignung zu prüfen, ein Anschreiben zu verfassen oder dich auf das Interview vorzubereiten.

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Beschreibung bereitgestellt von Avelios Medical

ABOUT US

Our mission at Avelios is to unlock clinical data to power seamless healthcare operations for better patient care. To do so, we have built a modular software platform that digitizes and optimizes workflows in hospitals with cutting-edge technology in a user-friendly way. With our software, we enable hospitals, doctors & nurses to provide their patients with the best possible care.
We are growing fast and want to keep expanding our team and business to fundamentally digitize healthcare for the better. We appreciate different backgrounds and see diversity as one of our strengths.

THE TEAM AND ROLE

As a Working Student Machine Learning (all genders), you will support the integration of intelligent systems into real-world clinical environments. Collaborating with our interdisciplinary development teams, your role will focus on contributing to bringing state-of-the-art models (LLMs, ASR, and more) into production and embedding them directly into Avelios software to improve everyday medical workflows. This is a unique opportunity to shape how AI transforms the way clinicians work.

 

YOUR RESPONSIBILITIES

  • Collaborate with our core development team to bring machine learning into production

  • Support the design and training of ML models on large-scale clinical datasets

  • Assist with the integration of AI-powered solutions (LLMs, ASR, RAG, Embeddings, and more) into real medical workflows

  • Support the evaluation, benchmarking, and fine-tuning of existing models for clinical use cases

  • Explore Federated Machine Learning frameworks for privacy-preserving model training

  • Collaborate with leading academic and research institutions

  • Contribute to the reliability, performance, and quality of AI features in production

  • Leverage access to high-performance computing infrastructure to build robust ML pipelines

 

YOUR QUALIFICATIONS

  • Currently enrolled in Informatics, Computer Science, or a related field

  • Strong coding background, especially in Python

  • Exposure to ML frameworks such as PyTorch, HuggingFace, LangChain, or Pydantic, including LLMs, ASR models, or RAG pipelines with vector databases (e.g. Qdrant)

  • Genuine interest in new technologies and their application to real-world challenges

  • Fluency in English, German is a plus

 

NICE TO HAVE

  • GitHub contributions

  • Publications at top conferences or demonstrated cutting-edge results in applied ML (e.g. Speech Recognition or NLP)

     

YOUR BENEFITS

  • Variety in your tasks and the opportunity to take ownership

  • Flexible working hours

  • Support for your personal development through continuous learning and feedback and high chances to transition into a full-time role if the collaboration is successful

  • An international, informal team structure in a motivating start-up atmosphere, allowing you to participate directly in our customer growth story and the overall success of Avelios

  • Ability to gain valuable hands-on experience in a startup backed by leading international VCs

  • A monthly meal allowance up to 75 euros, and Corporate Benefits that give you access to discounts from a wide range of providers in various areas

Wichtiges für Werkstudierende

Was diese Werkstudentenstelle im Bereich Tech in Munich für dich bedeutet: die Wochenstundenregeln, die Vorteile bei den Sozialabgaben und worauf internationale Studierende vor der Bewerbung achten sollten.

Wochenstunden

Werkstudierende dürfen während des Semesters bis zu 20 Stunden pro Woche arbeiten, in den Semesterferien Vollzeit. Wer das einhält, behält den Studierendenstatus und die Werkstudentenvorteile.

Werkstudenten-Regeln

Sozialabgaben

Dank des Werkstudentenprivilegs zahlst du keine Beiträge zur Kranken-, Pflege- und Arbeitslosenversicherung — nur die Rentenversicherung greift. Dir bleibt mehr netto als in einem regulären Job.

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Internationale Studierende

Studierende von außerhalb der EU dürfen 140 volle oder 280 halbe Tage im Jahr arbeiten (seit März 2024, zuvor 120/240). Ein Werkstudentenvertrag passt meist in diesen Rahmen — prüfe die genauen Grenzen auf deinem Aufenthaltstitel.

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