Senior Voice Model Engineer

16 hours ago

Chennai, Tamil Nadu, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

We are seeking a seasoned AI expert with hands-on experience in building and optimizing voice models for an Enterprise class voice solution domain.

Candidates will be working on developing, training, and refining AI models for voice synthesis, voice cloning, speech recognition, and/or voice transformation. The ideal candidate would be someone who has:

  • Developed and optimized text-to-speech models that achieved human-like voice synthesis, maintaining the unique style of voice actors across multiple languages.
  • Implemented real-time processing solutions that reduced inference time to under 1 second, enhancing user interaction and experience.
  • Managed large-scale datasets for voice cloning projects, ensuring high performance and reliability while supporting multilingual transcriptions.

The key responsibilities include:

  • Designing, developing, and fine-tuning deep learning models for voice synthesis (e.g., TTS, voice cloning).
  • Implementing and optimizing neural network architectures such as Tacotron, FastSpeech, WaveNet, or similar.
  • Collecting, preprocessing, and augmenting speech datasets.
  • Collaborating with product and engineering teams to integrate voice models into production systems.
  • Performing evaluation and quality assurance of voice model outputs.
  • Researching and staying current on advancements in speech processing, audio generation, and machine learning.

Required skills and qualifications:

  • A Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
  • Strong experience with Python and machine learning libraries (e.g., PyTorch, TensorFlow).
  • Hands-on experience with speech/audio processing and relevant toolkits (e.g., Librosa, ESPnet, Kaldi).
  • Familiarity with voice model architectures (TTS, ASR, vocoders).
  • Understanding of deep learning concepts and model training processes.

Preferred qualifications:

  • Experience with deploying models to real-time applications or mobile devices.
  • Knowledge of data labeling, voice dataset creation, and noise handling techniques.
  • Experience with cloud-based AI/ML infrastructure (e.g., AWS, GCP).
  • Contributions to open-source projects or published papers in speech/voice-related domains.

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