0Master's student in Machine Learning (m/f/d)
Hensoldt | Germany | 89xxx Ulm | Full time | Published since: 17.04.2026 on stepstone.de

Master's student in Machine Learning (m/f/d)

Branch: Electrical engineering Branch: Electrical engineering


HENSOLDT is a leading company in the European defence industry with global reach. Located in Taufkirchen near Munich, the company develops complete sensor solutions for defence and security applications. As a technology leader, HENSOLDT is driving the development of defence electronics and optronics and continuously expanding its portfolio on the basis of innovative approaches to data management, robotics and cyber security. Our products can be used in the areas of Space, Air, Land, Sea, Security, Cyber & Information Space. In 2023, HENSOLDT achieved sales of 1.85 billion euros. After the acquisition of ESG GmbH, the company employs about 8,500 employees. HENSOLDT is listed on the Frankfurt Stock Exchange in the MDAX. At the Ulm site, we are looking for a Machine Learning Pipeline for the Industrial Engineering department for the next possible time to predict test data from our products Masterand (w/m/d) in Machine Learning The Industrial Engineering department is responsible for the industrial feasibility of HENSOLDT's own products. This involves the development process in the context of the “Concurrent Engineering”, the series start-up phase, as well as the robust and scalable series production of existing products. The digitized processes and product data form the basis for this and are continuously improved. This master's thesis is based on the findings of a bachelor's thesis, which has demonstrated the basic feasibility of predictions for test data of products. In the master thesis, the systematic analysis of further machine learning models and their application to different product groups is to be carried out. The aim of the work is to develop the existing Machine Learning pipeline and to evaluate various machine learning models to optimize their application to different product groups and to enable more precise prediction of test data. Within the framework of this master thesis, a systematic analysis of the performance and suitability of various machine learning approaches is carried out to evaluate their potential in the context of the specific requirements of HENSOLDT products. The results of this evaluation are to be used to carry out cost-benefit assessment on the basis of which further investments and integration into the production processes of HENSOLDT can be discussed. .

Your tasks • Your profile • What we offer

Further development of a Machine Learning Pipeline for predicting test results for different assemblies in products Implementation of a cost/benefit estimate for the integration of this approach into our production processes

Student (w(/m/d) in the field of IT, natural sciences or electrical engineering Experience in programming with Python Knowledge about the use and implementation of machine learning models Teamable, communicative and independent working Very good knowledge of German and English Please upload your currently valid enrollment certificate for your application.

Flexible working hours & work-life balance Remuneration & social benefits Personal and professional development Working atmosphere Health and safety Mobility & Sustainability

Contact

ava Hensoldt
89077  Ulm
Germany
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The text of this ad was translated from German into English using an automatic translation system and may contain semantic and lexical errors. Therefore, it should be used for introductory purposes only. For more detailed information, see the original text of the ad at the link below.

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