Rf & Edge Ai Intern (video Analytics)

Analog Devices

Munich, Germany
Not specified; not specified; not specified
Not specified but likely onsite given the location and nature of the internship.
Train and evaluate drone-detection models
Build video pipelines with opencv or ffmpeg
Deploy optimized models on constrained edge platforms
Analog Devices is seeking a motivated RF & Edge AI Intern for a 4-6 month internship in Munich, Germany, focused on developing and validating video analytics for drone detection. The ideal candidate is a current Masters or PhD student with a background in engineering or computer science, solid machine learning foundations, and experience in video/computer vision tools

Job Summary

  • This internship focuses on building and validating video analytics for drone detection and situational awareness use cases on real hardware.
  • You will be expected to deliver a working demo plus a clear technical readout by the end of the 4-6 month period.
  • The program features close mentorship from a technical team and exposure to the full lifecycle from data to deployment.

Matching Summary

Match Score: 85

Analog Devices is seeking a motivated RF & Edge AI Intern for a 4-6 month internship in Munich, Germany, focused on developing and validating video analytics for drone detection. The ideal candidate is a current Masters or PhD student with a background in engineering or computer science, solid machine learning foundations, and experience in video/computer vision tools.

Salary

Not specified; Not specified; Not specified

Skills & Requirements

Must-have

  • Train and evaluate drone-detection models
  • Build video pipelines with OpenCV or FFmpeg
  • Deploy optimized models on constrained edge platforms
  • Design benchmarking experiments for accuracy and latency
  • Maintain structured data and experiment tracking
  • Python programming with PyTorch or TensorFlow

Nice-to-have

  • Experience with ONNX, TensorRT, or TFLite runtimes
  • Familiarity with embedded Linux deployment and profiling
  • Knowledge of YOLO-family or DETR architectures
  • Understanding of real-world sensing constraints
  • C/C++ programming for performance-critical work

Key Requirements

  • Current Masters or PhD student in Engineering or CS
  • Solid ML foundations in CNN-based vision models
  • Hands-on experience with Python and ML stacks

Work Rights

US Citizens, US Permanent Residents, or protected individuals may be exempt from export licensing review

Tailored Resume

Cover Letter