The DAMS Lab research group is looking for a student assistant (d/m/w) to join the team and help with group-internal prototype development and experiments in the context of system-oriented research on data and machine learning (ML) systems for the end-to-end data science lifecycle from data integration, cleaning, and preparation, over efficient and scalable model training, to model debugging and deployment. The tasks include supporting activities under supervision in the following areas:

• Open-source contributions to group-internal ML systems on high-level abstractions, compilation and runtime techniques, tests, as well as peripheral tools (APIs, system internals, and tools) [60%]
• Implementation of data analysis and ML pipelines developed at the chair (use cases, primitives, and applications from various domains, including health care and earth observation) [20%]
• Experimental evaluation of end-to-end ML pipelines, system components, and various baselines [20%]

Must criteria:

• Programming experience in Python, Java, and C++ (at least two)
• Basic understanding of data management, applied machine learning, compiler construction, distributed systems, and software engineering (at least two)
• Good knowledge of German and/or English required; willingness to acquire the respective missing language skills

Can criteria:

• Basic experience with version control systems (especially git) and open-source development workflows
• Basic knowledge of conducting experimental evaluations at system and component level
• Experience with R and shell scripts
• Ability to communicate and work in a team, independent working style, high motivation

Party responsible for specialist area / point of contact for job posting: Sarah Hashmi, hashmi@tu-berlin.de
Period of employment: from 01.09.2025, limited for two years
Apply to: jobs@dams.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.