ASR / Speech-to-Text Engineer Whisper Fine-Tuning + End-to-End System

I am looking for an experienced ASR engineer to build a production-ready speech-to-text system for a low-resource language. I already have approximately 3,000 prepared audio segments, totaling about 10 hours of audio, with clean and consistent transcripts ready for immediate use. Data preparation and segmentation are already handled. The initial 10 hours of audio will serve as the first milestone. After that, the engineer will be expected to continue training and improving the model with additional data until the system reaches a target WER of 10% or below. Your responsibility will focus on: Fine-tuning a Whisper-based model for high transcription accuracy Optimizing word error rate (WER) over time Providing inline/embedded start timestamps per phrase Building an efficient inference pipeline for both real-time and batch transcription Structuring evaluation and improvement workflows Preparing the system for deployment and integration into a web platform Providing clear documentation and guidance so I can independently continue training and improving the model over time without ongoing engineer involvement The goal is to reach strong accuracy at launch, with a clear process for continued improvement as more data becomes available. Please describe your experience with Whisper fine-tuning or similar ASR model training in your proposal.