Machine Learning Engineer for Time Series Classification

vor 1 Woche


Erlangen, Bayern, Deutschland Siemens AG Vollzeit

Mode of Employment: Limited

Unlock the Potential of Transfer Learning

As a Machine Learning Engineer, you will explore and implement transfer learning techniques for on-site training time series classification. You will develop an algorithm that can adapt to new data autonomously when deployed in the field. Additionally, you will identify the most hardware-efficient alternative combining tinyML techniques for the implementation on microcontrollers or AI-accelerators.

Key Responsibilities:

  • Develop and implement transfer learning techniques for time series classification
  • Design and implement an algorithm that can adapt to new data autonomously
  • Identify the most hardware-efficient alternative combining tinyML techniques
  • Integrate the solution to create real-world impact in an industrial application

Requirements:

  • Proficient in Python for developing machine learning models and implementing algorithms
  • Experience in C++ for implementing efficient and robust software solutions on embedded systems or AI accelerators
  • Strong background in machine learning, particularly in transfer learning and time series data analysis
  • Familiarity with data preprocessing, feature extraction, and concept drift detection techniques
  • Ability to integrate and test software on hardware platforms, ensuring efficient real-time performance

Make a Difference at Siemens

As an equal-opportunity employer, we welcome applications from diverse candidates. If you are interested in learning more about Siemens before applying, we encourage you to explore our website.



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