Software Development : Working Student AI Research and Infrastructure Support (m/f/d)

Your tasks

• Set up agent frameworks: Help with the installation and customization of AI agent tools.
• Benchmarking: Comparing the performance of AI models.
• Create data pipelines: Processing and transforming data to support the team.
• Provide multimodal tools: Integrating various data types for AI agents.
• Train classical ML models: Assist in training and validating models.
• Deploy inference services: Making models available in production.
• Monitoring and optimization: Participate in monitoring and improving model performance.
• Create documentation: Recording processes and results.
• Collaboration: Working with interdisciplinary teams.
• Evaluate technologies: Investigating new tools and methods in the AI field to support the team.

Your qualifications

• Current studies of computer science or a comparable field of studies with interest in AI and Machine Learning.
• Python skills: Experience in programming with Python.
• Git skills: Experience in working with Git environments and its tools.
• REST services: Ability to implement and utilize RESTful APIs (e.g. FastAPI).
• MCP services: Familiarity with implementing Model Context Protocol (MCP) services (e.g. FastMCP).
• Knowledge of LLMs: Understanding of Large Language Models and embedding models.
• RAG knowledge: Experience with Retrieval-Augmented Generation (RAG) methods.
• Classical ML approaches: Basic knowledge of classical machine learning techniques.
• Docker skills: Experience with Docker for containerizing applications.
• Data processing: Knowledge in data processing and analysis.
• Teamwork: Ability to collaborate in interdisciplinary teams.
• Problem-solving skills: Strong analytical and problem-solving abilities.
• Very good command of written and spoken English

Interested?

We are looking forward to receiving your application! The best way to apply is online using the reference number. If you have any questions, please feel free to contact your recruiting contact at any time.

You must be properly enrolled for the duration of your employment. You can work up to 20 hours per week during the lecture period. Mobile working is possible - but your main place of work is Munich.

We place great importance on equal opportunities. We look forward to receiving your application regardless of gender, nationality, ethnic and social origin, religion, ideology, disability, age as well as sexual orientation and identity.

Reference number: 14171
Recruiting contact: Emilia Kansik