Internship (Master Thesis) - Data & AI

Job vacancy: From now on

Description

FIRST IN MIND. FIRST IN CHOICE
Industrial Assembly Solutions is a division within Atlas Copco’s Industrial Technique business area. We offer multiple joining technologies from a single source and are a competence partner in innovative joining for the automotive and general industries worldwide. Our adhesive dispensing, self-pierce riveting and flow drill fastening are marketed under the product brands SCA, Henrob, K-Flow and Scheugenpflug. The Division is headquartered in Bretten, Germany with manufacturing in the United States, the United Kingdom, Germany and China.

We are seeking a motivated master’s student to join our research team for a thesis project focused on the combination of multiple Large Language Models (LLMs) for multimodal data ingestion. This project aims to explore and develop innovative methods for integrating various open-source LLMs to process and analyze multimodal data, including text, images, and other data types. The project would also consist of integrating the algorithm obtained within our MLOPs infrastructure.

Our current GenAI capabilities are limited to the ingestion of text only. Open-source algorithms, such as Villa, can perform semantic extraction from pictures. Additionally, when it comes to audio to text, or text to audio, algorithms such as Riva can be used. Before integrating such algorithms into our production pipeline, it is essential to evaluate the accuracy and behavior of such algorithm to couple it with the required guardrails. Upon the project completion, the intention is to integrate multimodal data ingestion capabilities in our official GenAI solution enabler, used by a wide range of users across the group.