Additionalinformation

Additional Information

• Be part of one of the fastest-growing and most visible Fintech startups in Europe, creating innovative services that have a substantial impact on the lives of our customers
• The ability to work with an international, diverse, inclusive, and ever-growing team that loves creating the best products for our clients
• Enjoy an office in the heart of Munich, located in a lively neighbourhood and close to the English garden
• All internships are worth the same with us: we also remunerate mandatory internships
• Learn and grow by joining our in-house knowledge sharing sessions
• Work productively with the latest hardware and tools
• Free subscription to the PRIME+ Broker

Companydescription

Company Description

Scalable Capital is a leading digital investment and banking platform with a full banking licence, empowering people across Europe to shape their own finances. Scalable Broker makes it easy and affordable for clients to invest professionally in stocks, ETFs, cryptocurrencies, and derivatives, as well as set up savings plans. Scalable Wealth, the digital wealth management service, offers clients professional investment in ETF portfolios, and is also adopted as a white-label solution by banks and other B2B partners. The company’s offerings are rounded off by attractive interest rates, loans, and private equity. With the European Investor Exchange, Scalable Capital offers an exchange specifically for retail investors. Over one million clients have already entrusted more than €30 billion to the platform. Founded in 2014, Scalable Capital now employs over 700 people across Munich, Berlin, Vienna, Milan, and London. Together with the founding and management team, including Erik Podzuweit and Florian Prucker, they are working on a new generation of financial services.

Visit our finance blog or check out our Social Media channels to find out what our Expert Teams have to say. Our Company Values guide us every day in how we work and collaborate. To learn more about them, you can find our values here (English).

Jobdescription

Job Description

• Enhance our ML/LLMOps and AI Agent infrastructure for model evaluation, testing, and deployment within an AWS environment.
• Evaluate and implement different LLM frameworks, AI agent architectures, and 3rd party APIs.
• Design and experiment with AI agent evaluation systems to measure reasoning quality, reliability, and consistency.
• Support the development and automation of AI agent systems and Retrieval-Augmented Generation (RAG) pipelines.
• Document your findings in our internal knowledge base
• Contribute to the development, improvement, and automation of our machine learning and data pipelines
• Gain experience in industry critical infrastructure technologies and apply them productively

Qualifications

• Excellent academic background in a quantitative discipline (computer science, machine learning, data science, financial mathematics,, engineering, physics, or a similar field)
• Currently pursuing a Bachelor’s or Master’s degree.
• First experiences with Cloud Infrastructure (AWS)
• Hands on experience in Python Fundamental knowledge in state-of-the-art LLM frameworks, RAG and vector databases (e.g. LangChain, LangGraph,, OpenSearch)
• First-hand experience with creating LLM-powered applications, AI agents, tool use, and multi-step reasoning workflows. (e.g. Chatbots, information retrieval, document summarization)
• Experience with ML packages in Python (e.g., pandas, numpy, scikit-learn, statsmodels)
• Curiosity and enthusiasm to learn new technologies and build reliable AI systems.
• Result-oriented and pragmatic way of working
• Fluency in English (written & spoken)
• Please also provide us with your latest transcript of records and if applicable your work references

Nice to have:

• Experience with AI Agent or RAG Evaluation Systems (e.g. LLM-as-a-judge, automated scoring pipelines, or Langfuse-based evaluation).
• Good understanding of software engineering principles, including API development, code versioning, and testing frameworks (e.g. Pytest, FastAPI, etc.)
• Familiarity with end-to-end ML projects
• Experience with Infrastructure as Code (IaC) like terraform is a plus
• Experience with CI/CD frameworks (e.g. Jenkins, Gitlab CI/CD) is a plus