AI Voice Expert

1 week ago

Surat, Gujarat, India beBeeVoiceEngineer Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Artificial Intelligence Voice Engineer

We are seeking an experienced AI voice engineer to join our team. The ideal candidate will have hands-on experience in building and optimizing voice models, specifically for voice synthesis and speech recognition.

The successful candidate will be responsible for designing, developing, and fine-tuning deep learning models for voice synthesis (e.g., TTS, voice cloning). They will also implement and optimize neural network architectures such as Tacotron, FastSpeech, WaveNet, or similar.

To succeed in this role, the candidate should have a strong background in Python and machine learning libraries (e.g., PyTorch, TensorFlow). Experience with speech/audio processing and relevant toolkits (e.g., Librosa, ESPnet, Kaldi) is also essential.

Key Responsibilities:

  • Design, develop, and fine-tune deep learning models for voice synthesis (e.g., TTS, voice cloning).
  • Implement and optimize neural network architectures such as Tacotron, FastSpeech, WaveNet, or similar.
  • Collect, preprocess, and augment speech datasets.
  • Collaborate with product and engineering teams to integrate voice models into production systems.
  • Perform evaluation and quality assurance of voice model outputs.
  • Research and stay current on advancements in speech processing, audio generation, and machine learning.

Requirements:

  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or 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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