For nearly 170 years, pioneering technologies and the business models developed from them have been the foundation of Siemens‘ success. Siemens’ central research and development unit – Corporate Technology – plays an important role in this. Corporate Technology (CT) develops Siemens’ technology and innovation strategy, creates and industrializes basic technologies, promotes business excellence through consulting and engineering services, and protects the company’s intellectual property.

CT is a strategic partner to Siemens’ operative units. It provides important services along the entire value chain – from research and development to production and quality assurance, as well as optimized business processes. The support provided to the businesses in their research and development activities is ideally balanced with CT’s own future-oriented research.

CT plays a key role in achieving and maintaining leading competitive positions in the fields of electrification and automation while at the same time helping Siemens fully tap into the growth field of digitalization. To ensure the success of these efforts, numerous experts around the world make their outstanding knowledge available to the company:

• Some 1,600 researchers based in North America, Europe, and Asia are hard at work on technologies that will have a broad impact on Siemens’ businesses, helping them successfully establish their innovations on the market.

• Some 5,100 software engineers spread across Asia, Europe, and the United States, helping the business units combine the real and virtual worlds with innovative software products and solutions.

• Finally, some 260 professionals drive business excellence at Siemens, helping to enhance the speed, agility, and efficiency of our company.

Otto-Hahn-Ring 6, Munich, Germany

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Junior Developer Cloud / IoT Software R&D
Otto-Hahn-Ring 6, Munich, Germany
In this internship, students will learn and apply cloud / IoT programming methods and state-of-the-art software technologies in industrial software development environments. They will work on ensuring that Analytics — Machine Learning — algorithms for predictive maintenance or optimization of industrial processes execute efficiently in the cloud or at the edge, close to data sources.…