Internship
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!
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!
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.
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
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
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
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.
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