TensorFlow Lite (TFLite) enables running ML models on mobile devices (iOS, Android) and edge hardware (Raspberry Pi, IoT). Models are quantized and optimized for inference speed and battery efficiency. Salary band: 110–170k USD. Time to learn: 4–6 weeks. Adjacent to TensorFlow, mobile development, and edge computing. High demand for on-device AI.
TensorFlow Lite (TFLite) is Google's lightweight machine learning framework for mobile and edge devices. It allows developers to run pre-trained models on Android, iOS, Raspberry Pi, and other constrained environments. TFLite handles model quantization, optimization, and provides APIs for inference in multiple languages (C++, Python, Swift, Kotlin). TFLite enables on-device ML: models run locally without server calls, providing privacy, latency benefits, and offline functionality. Applications include image recognition, object detection, pose estimation, speech recognition, and anomaly detection on edge devices.
| Region | Junior | Mid | Senior |
|---|---|---|---|
| USA | $90k | $145k | $190k |
| UK | $50k | $85k | $120k |
| EU | $55k | $90k | $130k |
| CANADA | $85k | $135k | $180k |
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