Senior Artificial Intelligence Engineer for Voice Development

4 days ago

Rajkot, Gujarat, India beBeeAIEngineer Full time ₹ 1,10,00,000 - ₹ 1,75,00,000

Achieve Human-Like Voice Synthesis

We are seeking an experienced AI Developer to build and optimize voice models for our client. The ideal candidate will have hands-on experience in developing and training deep learning models for voice synthesis, voice cloning, speech recognition, and/or voice transformation.

The successful candidate will design, develop, and fine-tune deep learning models for voice synthesis (e.g., TTS, voice cloning). They will implement and optimize neural network architectures such as Tacotron, FastSpeech, WaveNet, or similar. Additionally, they will collect, preprocess, and augment speech datasets, collaborate with product and engineering teams, perform evaluation and quality assurance of voice model outputs, and research current advancements in speech processing, audio generation, and machine learning.

Key Responsibilities:

  • Design and Develop Deep Learning Models: Create and refine deep learning models for voice synthesis, voice cloning, speech recognition, and/or voice transformation.
  • Optimize Neural Network Architectures: Implement and optimize neural network architectures such as Tacotron, FastSpeech, WaveNet, or similar.
  • Collect and Preprocess Speech Data: Collect, preprocess, and augment speech datasets for use in voice synthesis and voice cloning projects.
  • Collaborate with Teams: Collaborate with product and engineering teams to integrate voice models into production systems.
  • Evaluate Model Outputs: Perform evaluation and quality assurance of voice model outputs.
  • Research Advancements: Research current advancements in speech processing, audio generation, and machine learning.

Required Qualifications:

  • Bachelor's or Master's Degree: Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field.
  • Programming Experience: Strong experience with Python and machine learning libraries (e.g., PyTorch, TensorFlow).
  • Speech/Audio Processing Experience: Hands-on experience with speech/audio processing and relevant toolkits (e.g., Librosa, ESPnet, Kaldi).
  • Voice Model Architecture Knowledge: Familiarity with voice model architectures (TTS, ASR, vocoders).
  • Deep Learning Concepts Understanding: Understanding of deep learning concepts and model training processes.

Preferred Qualifications:

  • Real-Time Application Deployment Experience: Experience with deploying models to real-time applications or mobile devices.
  • Data Labeling and Noise Handling Experience: Knowledge of data labeling, voice dataset creation, and noise handling techniques.
  • Cloud-Based Infrastructure Experience: Experience with cloud-based AI/ML infrastructure (e.g., AWS, GCP).
  • Open-Source Project Contributions: Contributions to open-source projects or published papers in speech/voice-related domains.

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