Gboard Prediction Accuracy Enhancement
Publicada el 2026-07-16
Descripción de la oferta
I need a developer who can build a custom feature for Google’s Gboard that focuses squarely on improving the accuracy of its text-prediction engine. This isn’t a bug-fixing exercise or a simple integration; it is genuine feature development aimed at smarter, more context-aware suggestions while users type. Your job will start with analysing the existing prediction logic, then designing and implementing modifications—whether that means plugging in a new on-device language model, refining the current n-gram pipeline, or introducing lightweight neural-network tweaks that can run efficiently in real time. Kotlin or Java proficiency for the Android input-method framework is essential, and a solid grasp of NLP techniques, TensorFlow Lite (or similar), data handling, and privacy-first personalisation approaches will make the work smoother. Deliverables • Updated Gboard module (source + compiled APK) with measurable accuracy gains against the current baseline. • A repeatable test script or demo app that highlights side-by-side prediction results. • Brief technical report explaining model changes, datasets used, and any runtime or battery-impact considerations. I’ll consider the task complete once the new build consistently outperforms stock Gboard predictions on a representative corpus without noticeable latency. If this challenge excites you, let’s discuss your proposed approach and timeline.
Skills
Fuente original: freelancer