Werkstudent*in AI Inference & Platform Engineering (m/w/d/x)

Working student at Telekom Do you want to put the theory you have learned into practice and experience and help shape the digital world of tomorrow today? Then you've come to the right place! We can make and copy coffee ourselves. We are looking for working students like you who want to advance the connected world every day with team spirit and a willingness to innovate and perform!

T-Systems International GmbH

At T-Systems, we offer our business customers the right system solutions for their digital business. With our portfolio, we ensure that digital transformation reduces complexity, saves costs and makes everyday work easier. Our focus is connectivity, digital, cloud & infrastructure as well as security - Let's power higher performance!

About the position

With the Industrial AI Cloud, T-Systems is developing one of the most powerful AI infrastructures in Europe. Based on cutting-edge NVIDIA GPU systems, including DGX B200 and B300, we enable companies to operate large language models (LLMs) and generative AI applications securely, scalably and with high performance. We are looking for a dedicated working student AI Inference & Platform Engineering to join our AI Foundation team. You help us develop, deploy, and optimize LLM inference services on our Industrial AI Cloud. Together with experienced AI and platform engineers, you will work on scalable and powerful AI services for corporate customers. The position is aimed at students in computer science or related fields with good Python skills, initial experience in machine learning or backend development, and an interest in modern AI infrastructure.

Your main tasks:

We are looking for enrolled students to support our team in Hamburg from 01.01.2027 for at least 6 and a maximum of 24 months with up to 20 hours per week with the following tasks:

• Support in developing, deploying, and testing LLM inference services on the T-Systems AI Foundation platform
• Develop Python-based tools, scripts, and APIs to automate model deployments and operational processes
• Conduct performance benchmarks for LLMs and analyze latency, throughput, and resource utilization
• Collaboration in the integration and evaluation of modern LLM serving frameworks such as vLLM, sGLang and NVIDIA Dynamo
• Develop and optimize backend services and APIs for AI applications
• Helping you deploy containerized applications with Docker and Kubernetes
• Development of data pipelines and analyses to evaluate performance and operational metrics
• Investigation of optimization techniques such as KV caching, continuous batching, and efficient GPU usage
• Collaboration on automated tests, CI/CD pipelines, and technical documentation
• Working with experienced AI engineers to integrate new AI models and technologies

That's what you bring with you

You are studying a bachelor's or master's degree in computer science, artificial intelligence, software engineering, mathematics or a comparable degree program You also have the following knowledge and skills:

• Good programming skills in Python and practical experience with software development, automation or data processing
• First practical experience in software development, machine learning, data engineering or backend development through professional activities, internships or own projects
• Knowledge of Python libraries such as NumPy, pandas, scikit-learn or comparable frameworks
• Basic knowledge of backend development, REST APIs, and modern software development practices
• Experience with Git, Docker, and Linux-based development environments
• Basic understanding of machine learning, model evaluation and performance benchmarking
• Analytical thinking, structured working methods and enjoyment of complex technical challenges
• Personal initiative, ability to work in a team and interest in the development of modern AI technologies
• Good English language skills

Nice-to-have

• Experience with Python backend frameworks such as FastAPI
• First points of contact with large language models, generative AI, or model inference
• Basic knowledge of LLM serving frameworks such as vLLM, sGLang, or Tensorrt-LLM
• Kubernetes and container orchestration skills
• Experience with CI/CD tools such as GitHub Actions
• Knowledge of SQL, databases, and data pipelines
• Experience with asynchronous Python programming, caching, or performance optimization
• Interest in NVIDIA GPU technologies, distributed systems, and high-performance computing
• Basic knowledge of monitoring and observability

What we offer

• Collaboration on one of Europe's largest AI infrastructure platforms
• Insights into cutting-edge NVIDIA GPU infrastructure, including DGX B200 and B300
• Practical experience with current LLM inference technologies such as vLLM, sGLang, NVIDIA Dynamo, and Tensorrt-LLM
• Ability to build skills in AI inference, GPU computing, Kubernetes, and productive AI systems
• Close collaboration with experienced AI engineers, software developers and platform specialists
• Collaboration on real AI services for corporate customers
• Flexible working hours that are compatible with your studies
• An innovative work environment with diverse learning and development opportunities

This position is also available on a part-time basis. Severely disabled people are given priority if they are equally qualified.