Working Student Industrial Iot

vor 3 Wochen


Munich, Deutschland ALPS ELECTRIC EUROPE GmbH Vollzeit

ALPS ALPINE EUROPE

Unterschleißheim, AAEU MN

Stundenweise

Publiziert: 01.03.2023

**PERFECTING THE ART OF ELECTRONICS**:

- The
**ALPS ALPINE EUROPE GmbH** belongs to the Japanese
**ALPSALPINE CO. LTD.** established in 1948. Our philosophy is “Perfecting the Art of Electronics” - hence ALPS ALPINE CO. LTD. is one of the biggest independent global manufacturers of high-quality electronic and electro-mechanical components for vehicles, mobile devices, home electronics and industrial equipment. Our European Head Office in Unterschleissheim near Munich co-ordinates the sales, marketing and product engineering activities of our offices in Dusseldorf, Stuttgart, Wolfsburg, Paris, Milton Keynes, Coventry, Gothenburg, Frölunda and Milan, as well as the production in our manufacturing site in Dortmund. Our customers are automakers, TIER1 suppliers and other global players. ALPS ALPINE CO. LTD counts around 42.000 employees worldwide and at present about 740 employees are working for ALPS ALPINE EUROPE GmbH.
To strengthen our Engineering Team at our location in Unterschleißheim near Munich, we are looking for an engaged
**Working Student Industrial IoT - Machine Learning** (M/F/d) with immediate effect.

**YOUR CHALLENGES**:

- As a working student in the field of industrial IoT, you have the opportunity to get involved in Research & Development activities to define the future direction and technology to be used for our next generation asset tracking product line and to work with highly motivated and extremely ambitious colleagues. We offer you the opportunity to work on exciting projects right from the start and actively contribute your creative ideas. Your tasks and responsibilities will be:

- Explore the applicability of integrating various environmental sensors with Machine Learning Cores into our future product line-up
- Make sense of data from various MEMS sensors and identify ways to fuse them together for motion detection and classification use-cases
- Develop machine learning algorithm using tools such as Scikit Learn, TensorFlow, PyTorch and EdgeImpulse
- Contribute to setting up and extending the machine learning algorithm development tools and test infrastructure
- Develop code (Embedded C) to integrate the algorithm into resource constrained Cortex-M series MCUs to act as Edge-Algo-Processor

**YOUR PROFILE**:

- Currently enrolled as a Bachelor or a Master student of Electrical Engineering, Information Technology, Computer Science or related studies
- Terms such as Central Limit Theorem, Kalman Filtering, Decision Tree Classifiers and Real-Time Edge Computing are familiar to you
- Working knowledge in C, C++, Python & Matlab
- Experience in embedded firmware development
- Familiarity with any machine learning toolkit such as Scikit Learn, TensorFlow, PyTorch or EdgeImpulse is an added advantage
- Exposure to maker platforms such as Arduino and Raspberry-Pi would be beneficial
- Passion for learning new technologies
- Inquisitive mindset and an abundant curiosity to venture into the unknown
- Intercultural & communication skills
- A very good command of English
- Availability for 1 year minimum, 20 hours per week, working partially on site

**OUR OFFER**:
The high standards which build the guideline for ourselves as well as for the quality of our products are also set for our employees. Nevertheless, demand and support go “hand in hand” at ALPS ALPINE and we always appreciate our colleagues’ commitment and passion This is why we offer numerous benefits alongside attractive salaries. Being a caring employer, our 24/7 accident insurance covers all our employees before, during and after work. In order to support our employees in the best way, we take care of professional structured onboardings. We are characterized by an international and creative working environment with fast decision-making processes, open communication, an appreciative feedback culture. Modern workstations, remote working and free drinks are available.



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