Fraunhofer-Gesellschaft

Scientist, Machine Learning for Sensor Systems

Fraunhofer-Gesellschaft

full-time

Posted on:

Location Type: Office

Location: München • Germany

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Tech Stack

PythonPyTorchTensorflow

About the role

  • Developing and implementing machine learning and deep learning models for evaluating sensor data
  • Preprocessing and analyzing time- and frequency-domain sensor data (signal processing, feature engineering)
  • Setting up and maintaining data pipelines: sensor data acquisition, storage (e.g., databases), and processing
  • Using Python (including TensorFlow, PyTorch) for ML applications, model training, evaluation, and deployment
  • Using GPU-based servers and modern IT infrastructure for training and inference
  • Applying classical ML methods (e.g., regression, classification) and neural networks (e.g., CNNs, RNNs)
  • Preparing ML models for inference on edge systems (edge AI, embedded AI)
  • Collaborating on MLOps/DevOps processes (e.g., versioning, automation, CI/CD)
  • Participating in national and international research projects
  • Publishing results in journals and at conferences
  • Creating structured technical documentation of development results

Requirements

  • Completed university degree, preferably in computer science, electrical engineering, or a comparable field
  • Strong programming skills in Python (e.g., TensorFlow, PyTorch)
  • In-depth knowledge of machine learning/deep learning (statistics and data analysis)
  • Good knowledge of sensor technology and sensor applications
  • Experience handling sensor data and sensor networks, including data collection, storage, and processing
  • Ideally, initial experience with DevOps/MLOps approaches
  • Experience with techniques for reducing ML model size and complexity to enable deployment on constrained hardware
  • Strong analytical and solution-oriented mindset
  • Independent, structured, and self-reliant working style
  • Excellent communication skills for collaborating with industry partners and project teams
Benefits
  • Opportunity to pursue a doctorate (PhD)
  • Collaboration within an interdisciplinary and dedicated research team
  • Access to modern computing resources and research infrastructure
  • Flexible working hours and opportunities for personal development
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learningdeep learningPythonTensorFlowPyTorchsignal processingfeature engineeringMLOpsDevOpsdata pipelines
Soft Skills
analytical mindsetsolution-oriented mindsetindependent workingstructured workingself-reliant workingexcellent communication skills