AI Voice Model Developer

5 days ago

Ghaziabad, Uttar Pradesh, India beBeeArtificial Full time ₹ 1,00,00,000 - ₹ 2,00,00,000
Job Description

A highly skilled professional with expertise in Artificial Intelligence is required to work on developing and refining AI models for voice synthesis, speech recognition, and voice transformation.

The ideal candidate would have experience in building and optimizing voice models, managing large-scale datasets for voice cloning projects, and implementing real-time processing solutions.

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 cross-functional 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.
Required Skills and Qualifications

To be successful in this role, the ideal candidate should possess the following skills and qualifications:

  • 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

The following qualifications are preferred but not required:

  • 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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