How do I apply for the Internship - AI/ML Engineering (m/f/x) position at Scalable Capital and track my application?

We provide a direct link to the official application portal. You can apply directly here . Additionally, you can easily track this and other applications by clicking the bookmark icon to save it to your YGI Kanban board .

What are the working arrangements and expected duration for the Internship - AI/ML Engineering (m/f/x) role?

This position is a not disclosed, structured as a not disclosed role, with an expected duration of 3 months.

What educational background or degree level is required for the Internship - AI/ML Engineering (m/f/x) at Scalable Capital?

Candidates are generally expected to be holding or pursuing the following degree levels: Bachelor, Master.

Does Scalable Capital provide visa sponsorship or assistance for international applicants?

Regarding visa assistance and sponsorship for this role, the official status is currently listed as: Not disclosed.

Internship - AI/ML Engineering (m/f/x)

Scalable Capital

Found 1 month ago

Location

Munich, Germany

Duration (Months)

3 Months

Time

Not disclosed

Work Mode

Not disclosed

Salary

Not disclosed

Visa Help

Not disclosed

Last Verified

1 month ago

Education

Bachelor
Master

Skills & Qualifications

Technical Skills

AWS
Python
LLM frameworks
RAG
vector databases
LangChain
LangGraph
OpenSearch
Chatbots
information retrieval
document summarization
pandas
numpy
scikit-learn
statsmodels

Soft Skills

Curiosity
enthusiasm
Result-oriented
pragmatic way of working

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

Requirements

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

AI & Machine Learning

Applied Machine Learning

Languages

English

Nice to Haves

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

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