Internship (Master Thesis) - Data & AI

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. 
 

Main responsibilities: 

• Conduct a comprehensive literature review on multimodal data ingestion and the use of LLMs.
• Design and implement a framework for combining multiple open-source LLMs to handle multimodal data.
• Develop and test algorithms for data preprocessing, model integration, and performance optimization.
• Evaluate the performance of the proposed methods using benchmark datasets.
• Document research findings and contribute to internal publications.
• Present progress and results to the internal AI community team.

Experience requirements:

• Currently enrolled in a master’s program in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Background in machine learning, natural language processing, and deep learning.
• Experience with open-source LLMs (e.g., GPT, BERT, LLAMA) and multimodal data processing.
• Proficiency in programming languages such as Python and familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch).
• Advanced analytical, problem-solving, and communication skills.
• Ability to work independently and collaboratively in a research environment.
• Experience with Hugging Face models use and contribution is a plus.

Your benefits:

• Motivating environment:
  in a strong international team that enjoys a lot of freedom
• Focus on your strengths:
  for example, with coaching and individual training programmes
• Fitness on the job:
  through our health management with monthly changing campaigns
• Family friendliness:
  thanks to flexitime and home office option

Diverse by nature and inclusive by choice
Bright ideas come from all of us. The more unique perspectives we embrace, the more innovative we are. Together we build a culture where difference is valued and we share a deep sense of purpose and belonging.  

Direct - your connection to us:

Do you have any questions?
We look forward to receiving your e-mail!
IAS.career@atlascopco.com

Atlas Copco IAS GmbH
Jana Heller

Human Resources