Privacy-Preserving IoT IDS Development

I need an expert to develop a privacy-preserving and anomaly detection for Intrusion Detection System (IDS) for IoT networks.

The system should leverage:
- Semi-supervised learning
- Unsupervised feature extraction
- Federated learning

Key functionalities include:
- Anomaly detection using an autoencoder
- K-Means clustering
- Distributed training across edge devices

Ideal skills and experience:
- Strong background in machine learning and cybersecurity
- Experience with federated learning and anomaly detection
- Familiarity with IoT networks and privacy-preserving technologies

Please provide relevant work experience.