Speech Scientist

Role: AI Engineer Location- Remote Job Description- Looking for strong AI Engineer for experience to assist with the AI Voice project. We are seeking a skilled and innovative AI Engineer with hands-on experience in building and optimizing voice models. In this role, you will work on developing, training, and refining AI models for voice synthesis, voice cloning, speech recognition, and/or voice transformation. Your work will contribute to cutting-edge applications in conversational AI, voice assistants, and generative audio. 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. • 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. 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. Required 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 • 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.