Student assistant (80 hours per month)

The DEEM Lab (https://deem.berlin) conducts research at the intersection of data engineering and machine learning. Our goal is to develop efficient data systems for AI and machine learning applications that are easy to use while simultaneously guaranteeing the fundamental rights of users (such as the "right to be forgotten").

We are looking for support for our BIFOLD project. The aim of the project is to develop an efficient runtime for data science pipelines.

• Support with implementing features and optimizations (50%)
• Support with modifying and extending skrub components as needed (30%)
• Support with writing tests and benchmarks (20%)

The student assistant will also be included as a co-author on resulting scientific publications.

Required Qualifications:

• Solid knowledge of machine learning (concepts, models, and workflows)
• Proficiency in Python
• Experience using libraries (scikit-learn, pandas, polars, or PyTorch)
• Strong understanding of scalable data processing
• Working knowledge of at least one systems programming language (Java, C++, or Rust)
• Prior experience contributing to data systems or machine learning frameworks
• Good knowledge of German and/or English required; willingness to acquire the respective missing language skills

Nice to Have:

• Prior exposure to open-source development practices or contributions to open-source projects

Party responsible for specialist area / point of contact for job posting: Prof. Dr. Sebastian Schelter - sekr@deem.tu-berlin.de
Period of employment: immediately limited to 2 years
Apply to: sekr@deem.tu-berlin.de

Please submit your written application including cover letter, your CV, certificate of enrollment, and where applicable, current transcript of records, with the reference number to the place of employment indicated above.
In the interest of promoting equality opportunities for men and women, applications from women with suitable qualifications are particularly encouraged.