Gen AI Audio Researcher

We are looking for a Gen AI Researcher for Audio to join our team and help develop next-generation voice synthesis models. You'll research and build deep learning systems that can generate expressive, natural-sounding speech from text or audio prompts, and collaborate with cross-functional teams to integrate your work into production-ready pipelines.

Key Responsibilities

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Research and develop state-of-the-art voice synthesis models (e.g., TTS, voice cloning, speech-to-speech).

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Build and fine-tune models using frameworks like PyTorch and HuggingFace.

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Design training pipelines and datasets for scalable voice model training.

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Explore techniques for emotional expressiveness, multilingual synthesis, and speaker adaptation.

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Work closely with product and creative teams to ensure models meet quality and production constraints.

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Stay on top of academic and industrial trends in speech synthesis and related fields.

Must Haves

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Strong background in machine learning and deep learning, with focus on speech/audio.

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Hands-on experience with TTS, voice cloning, or related voice synthesis tasks.

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Proficiency with Python and PyTorch; experience with libraries like torchaudio, ESPnet, or similar.

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Experience training models at scale and working with large audio datasets.

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Familiarity with vocoders and transformer-based architectures.

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Strong problem-solving skills, ability to work autonomously in a remote-first environment.

Nice to Have

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PhD degree in Computer Science/ Machine Learning and publications in top venues.

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Contributions to open-source speech research or participation in relevant benchmarks.

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Familiarity with adjacent areas like lip-syncing, audio-driven animation, or expressive speech control.

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Experience with voice datasets or proprietary pipelines.