Internship Machine Learning (f/m/x)

München

ZEISS Group

ZEISS is an international leading technology enterprise operating in the optics and optoelectronics industries. 

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Your role

You will play a crucial role in bringing new ML and CV functionality to our new revolutionary digital microscopy online platform at ZEISS. Together with our team of software developers and machine learning engineers you will work on improving our automated machine learning and computer vision toolset. You will have the possibility to improve your knowledge in areas such as automated ML pipelines, scalable ML infrastructure or our framework for training computer vision algorithms. As the leading microscopy company, we have an unlimited number of use cases for ML and CV. Datasets ranging from neuron and other cell biology images to microscopic images acquired in industrial quality labs provide us with exciting new challenges every day.

Your profile
  • finding pleasure in developing production-ready software in Python, demonstrated by a portfolio of projects

  • active user of version control (git)

  • good understanding of the principles of modern Deep Learning and Computer Vision algorithms

  • proven track record of contributing maintainable code to team projects or open-source projects

  • deep curiosity and willingness to dive into new subject areas

  • self-motivated personality, independent working style and collaborative mindset

  • fluent in English or German

The following will be considered an advantage
  • proficiency in a second object-oriented programming language with portfolio of projects (e.g. C++, C#)

  • portfolio of ML projects (e.g. on Kaggle)

  • familiarity with MLOps

  • familiarity with Azure

  • familiarity with CI/CD

  • familiarity with Docker

Your ZEISS Recruiting Team:

Laura Steininger, Trami Le
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Tags: Azure Biology CI/CD Computer Vision Deep Learning Docker Git Industrial Machine Learning ML infrastructure MLOps OOP Open Source Pipelines Python

Region: Europe
Country: Germany
Job stats:  72  13  0

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