Join us as a Working Student Machine Learning (Generative AI)

Join our AI journey at Kodex AI
Send your application to
Claus Lang, CTO Kodex AI
Claus Lang
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Kodex AI is at the cutting edge of AI technology in the financial industry. We are a young VC-funded startup with a vision to revolutionize the financial industry by cutting out tedious manual tasks by up to 90%. We are building an LLM-powered assistant that is not only versatile and intelligent but also attuned to the precise needs of the industry. Now, we're looking for several tech-focused working students to join our talented and growing team in our Berlin office.

About the Role:

You will work close to and learn from our highly skilled senior data scientist and the rest of the team to help scale our product from the first few users to thousands. You will apply the latest developments in Generative AI.

There are numerous exciting challenges around Generative AI and Large Language Models (LLMs) waiting for you, for example:

  • Fine-tuning of our open-source based LLM: Assist in the optimization of our proprietary Large Language Model (LLM) which is specifically fine-tuned for the financial industry, ensuring it combines sector-specific language expertise with deep domain knowledge.
  • Internal Knowledge Graph: Contribute to the enhancement of our industry-leading knowledge graph technology, ensuring it provides a comprehensive view of relevant internal information and integrates human domain knowledge into the Generative AI models.
  • AI Guardrails: Assist in the development and maintenance of AI guardrails to ensure the safe and ethical use of AI, providing an extra layer of protection against data breaches and compliance issues.
  • Multimodality: Research and combine the most promising models and approaches to upskill our model to understand and generates not only text but also visual data like graphs and images as well as quantitative data like CSV files.

It will be your job to research concepts and algorithms, gather data, run experiments, and help bring the best approach into production.

What you'll need:

  • An ongoing Bachelor's or Master's degree or Ph.D. in Data Science, Computer Science, Mathematics, or a related field
  • Some experience in applying AI and machine learning techniques outside of academia, bonus points for experience with LLMs or similar models
  • Proficiency in python and relevant ML-related python libraries
  • Great problem-solving skills, a collaborative mindset, and a passion for experimentation and innovation
  • Pragmatic mindset and readiness to iterate quickly
  • Willingness and ability to learn new technologies
  • Good English communication and ability to work efficiently with other tech team members
  • Based in Berlin

Why join Kodex AI?

You'll join a forward-thinking team that's driven by a passion for disrupting the status quo. We offer a competitive salary (including significant employee stock options), flexible working conditions, and an attractive benefits package, including an Urban Sports Club membership.

Diversity & Inclusion at Kodex AI

Kodex AI is an equal-opportunity employer, celebrating diversity as a source of strength. We encourage applications from candidates of all backgrounds. We welcome applications from candidates of all backgrounds, without discrimination. Our commitment to diversity aligns with our vision for a team that mirrors the vibrant society in Berlin. We actively work towards this goal, driven by a dedication to foster an inclusive work environment, where every voice is heard, valued, and respected. Your unique perspective matters, and we are committed to listening, learning, and evolving to create a genuinely inclusive workplace.

Our Values Shape Everything We Do

AI Native

We use AI tools and software to work smarter and more efficiently

No Bullshit

Our ideas and opinions are backed by arguments and we communicate explicitly


Every employee is an owner of Kodex AI and an owner of their work


We measure what matters most to improve our decision making

Continuous Improvement

We are not afraid of taking calculated risks as long as we learn from our failures


We brutally prioritise for value-add to maximize execution speed