Internship - AI/ML Engineering (AI)

Location: Berlin, Germany; hybrid workplace

Company

Digital investment and banking platform offering brokerage, wealth management, savings, lending, private equity, and exchange services across Europe.

What you will do

• Enhance ML/LLMOps and AI agent infrastructure for model evaluation, testing, and deployment in AWS.
• Evaluate and implement LLM frameworks, AI agent architectures, and third-party APIs.
• Design and experiment with AI agent evaluation systems measuring reasoning quality, reliability, and consistency.
• Support the development and automation of AI agent systems and Retrieval-Augmented Generation pipelines.
• Contribute to machine learning and data pipelines and document findings in the internal knowledge base.
• Apply experience with industry-critical infrastructure technologies in product development.

Requirements

• Excellent academic background in computer science, machine learning, data science, financial mathematics, engineering, physics, or a similar quantitative discipline.
• Currently pursuing a Bachelor’s or Master’s degree.
• First experience with AWS cloud infrastructure and hands-on experience with Python.
• Fundamental knowledge of modern LLM frameworks, RAG, and vector databases such as LangChain, LangGraph, and OpenSearch.
• First-hand experience creating LLM-powered applications, AI agents, tool-use systems, and multi-step reasoning workflows, such as chatbots, information retrieval, or document summarization.
• Experience with Python ML packages including pandas, numpy, scikit-learn, or statsmodels.
• Curiosity, enthusiasm for learning new technologies, and a pragmatic, result-oriented way of working.
• Fluency in written and spoken English.
• Latest transcript of records and, if applicable, work references.

Nice to have

• Experience with AI agent or RAG evaluation systems, including LLM-as-a-judge, automated scoring pipelines, or Langfuse-based evaluation.
• Understanding of software engineering principles, API development, code versioning, and testing frameworks such as Pytest or FastAPI.
• Familiarity with end-to-end ML projects.
• Experience with Infrastructure as Code such as Terraform.
• Experience with CI/CD frameworks such as Jenkins or GitLab CI/CD.

Culture & Benefits

• International, diverse, inclusive, and growing working environment.
• Mandatory internships are remunerated.
• In-house knowledge-sharing sessions supporting learning and growth.
• Access to the latest hardware and tools.
• Free PRIME+ Broker subscription.