Artificial Intelligence Voice Specialist

4 days ago


Coimbatore, Tamil Nadu, India beBeeVoice Full time ₹ 1,00,00,000 - ₹ 2,00,00,000
Senior Voice Model Engineer">

We are seeking an experienced Senior Voice Model Engineer to develop and optimize voice models for our Enterprise class voice solution domain.

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The ideal candidate will have hands-on experience in building and optimizing voice models, with a strong background in deep learning concepts and model training processes.

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Key Responsibilities:

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

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

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

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Work Mode: Remote

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Others:

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An 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.

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They should have implemented real-time processing solutions that reduced inference time to under 1 second, enhancing user interaction and experience.

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They must have managed large-scale datasets for voice cloning projects, ensuring high performance and reliability while supporting multilingual transcriptions.

"]],

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