Stellenangebot

Intern/Working Student – Computer Vision & Deep Learning (m/w/d)

Stellenbeschreibung:

The "Realtime Computer Vision" (RCV) group at Robotron Datenbank Software GmbH creates a modular platform with considerable flexibility that uses Artificial Intelligence and highly-sophisticated deep learning algorithms to implement diverse computer vision use cases. Whether it is the optimization of quality control inspections, acceleration of test processes or automatic detection of objects - RCV provides wide range of services for a multitude of prevailing operational issues. For more details, visit https://www.robotron.de/produkte/rcv

The group is looking for motivated students with a strong background in programming and application development to join the team as interns or working students. This is a position for those interested in building products that use Computer Vision in their core. These products will be used to serve end customers and as well internal development. Some of the things we use every day to build our products include Python, TensorFlow, PyTorch, Docker. If you have experience with or are interested in learning more about any of these, then this might be the right place for you.

Land:
Deutschland
Standorte:
Dresden
Karrierelevel:
Praktikant
Werkstudent
Kategorie:
Softwareentwicklung
Fachgebiet:
IoT
Geschäftsbereich:
Industrie
Zeitmodell:
Vollzeit oder Teilzeit
Vertrag:
befristet
Tätigkeitsschwerpunkte:

What we have to offer:

  • Practical experience with innovative and interesting use cases
  • Deep insights in the implementation of the state of the art
  • Young and innovative team working environment
  • Final thesis - with an innovative industry partner
Anforderungen:
  • Studying Informatics, Computer Science, Artificial Intelligence or comparable studies
  • Practical experience in coding with Python
  • Knowledge about web frameworks for building APIs with Python
  • Good knowledge with image processing and computer vision
  • Ideally, experience in the field of machine learning
  • Structured and analytical way of working
Bewerbungsinformationen:

The working time for working students during the lecture period is a maximum of 20 h/week, within the lecture-free period an extension up to 40 h/week is possible. The activity should cover a period of at least 3 months, ideally you will support us for a whole semester.

Jetzt bewerben
Zurück
Personalabteilung: Solveig Surner und Isabel Belger
Ihre Ansprechpartner:
Solveig Surner und Isabel Belger
Personalreferat
HR Assistent

Informationen zum Datenschutz und zum Umgang mit Ihren personenbezogenen Daten finden Sie hier.

nach
oben