Freelance Developer for Whisper Model Setup and Integration in Learning App
Budget: $750 – $1,500 USD
Job Description:
We are looking for an experienced Machine Learning Developer to help integrate OpenAI's Whisper model into our English learning app. The ideal candidate will have expertise in AI, deep learning, and model deployment, specifically with Whisper or other speech-to-text models.
Responsibilities:
• Set up and deploy the Whisper Small or Medium model for speech-to-text conversion in our learning app.
• Optimize the model for real-time transcription and feedback on pronunciation errors.
• Integrate the model with the app’s existing backend and ensure seamless functionality.
• Assist in building a system that provides feedback to users based on their speech accuracy.
• Collaborate with our development team to ensure proper API integration and performance tuning.
Requirements:
• Proven experience with machine learning and AI model deployment.
• Familiarity with Whisper or other speech recognition models (e.g., Google STT, Azure STT).
• Proficiency in Python, PyTorch, and experience working with GPUs.
• Strong understanding of API integration and app development.
• Ability to optimize the model for low-latency, high-accuracy performance.
• Prior experience with real-time speech processing is a plus.
Preferred Skills:
• Experience with CUDA and TensorFlow.
• Understanding of real-time audio processing.
• Familiarity with Docker or Kubernetes for deployment.
• Experience with Kaldi, Praat, Pydub is an advantage
Project Scope: This is a freelance project-based role with the possibility of ongoing collaboration. Our target audience is Vietnamese learners of English, and the key objective is to create a tool that provides real-time feedback on pronunciation.
How to Apply: Please provide examples of relevant projects where you've deployed machine learning models, especially for speech-to-text. Include a brief explanation of how you’d approach this project and your expected timeline for completion.
We are looking for an experienced Machine Learning Developer to help integrate OpenAI's Whisper model into our English learning app. The ideal candidate will have expertise in AI, deep learning, and model deployment, specifically with Whisper or other speech-to-text models.
Responsibilities:
• Set up and deploy the Whisper Small or Medium model for speech-to-text conversion in our learning app.
• Optimize the model for real-time transcription and feedback on pronunciation errors.
• Integrate the model with the app’s existing backend and ensure seamless functionality.
• Assist in building a system that provides feedback to users based on their speech accuracy.
• Collaborate with our development team to ensure proper API integration and performance tuning.
Requirements:
• Proven experience with machine learning and AI model deployment.
• Familiarity with Whisper or other speech recognition models (e.g., Google STT, Azure STT).
• Proficiency in Python, PyTorch, and experience working with GPUs.
• Strong understanding of API integration and app development.
• Ability to optimize the model for low-latency, high-accuracy performance.
• Prior experience with real-time speech processing is a plus.
Preferred Skills:
• Experience with CUDA and TensorFlow.
• Understanding of real-time audio processing.
• Familiarity with Docker or Kubernetes for deployment.
• Experience with Kaldi, Praat, Pydub is an advantage
Project Scope: This is a freelance project-based role with the possibility of ongoing collaboration. Our target audience is Vietnamese learners of English, and the key objective is to create a tool that provides real-time feedback on pronunciation.
How to Apply: Please provide examples of relevant projects where you've deployed machine learning models, especially for speech-to-text. Include a brief explanation of how you’d approach this project and your expected timeline for completion.