The Speech & Language Scientist is a specialized role that focuses on advancing the understanding and application of speech and language technologies. This role bridges research and development, enabling cutting-edge innovations in areas such as automatic speech recognition (ASR), natural language understanding (NLU), speech synthesis (TTS), and conversational AI.
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Responsibilities
- Conduct cutting-edge research in speech and audio technologies, including areas such as speech recognition, speech synthesis, audio enhancement, speaker identification, and spatial audio.
- Research, model, design, develop and test novel audio and speech processing algorithms using machine learning, signal processing, and computer vision.
- Collaborate with cross-functional teams (e.g., software engineers, product managers, and designers) to implement research into real-world applications.
- Propose scenarios where AI techniques could improve the efficiency of target clients’ businesses.
- Invent, analyze, design, develop, and optimize algorithms and models in audio areas such as Speech Recognition, Text to Speech, Speaker Recognition, etc.
Qualifications
- Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on speech and audio processing, or equivalent practical experience.
- Proven track record of research in speech or audio processing, demonstrated by publications in peer-reviewed journals or conferences.
- Expertise in machine learning frameworks (e.g., PyTorch, TensorFlow) and proficiency in programming languages like Python, C++, or similar.
- Strong knowledge of signal processing techniques and deep learning models for speech and audio tasks.
- Proven track record of research in speech or audio processing, demonstrated by publications in peer-reviewed journals or conferences.
Preferred Qualifications
- Experience with real-time audio systems or applications in AR/VR, accessibility, or social interaction platforms.
- Familiarity with techniques for multilingual or low-resource speech recognition.
- Background in self-supervised or unsupervised learning for speech/audio representation.
- Knowledge of privacy-preserving techniques in audio data processing.
- Experience mentoring junior researchers or managing collaborative projects.
