TTS Research Scientist

Representative responsibilities/duties will include but not limited to:

·       Design and optimize text/NLP preprocessing pipelines with Deep Learning or Machine Learning methods, including Grapheme-to-phoneme (G2P) conversion for multilingual support; Text normalization; polyphone disambiguation; Prosody prediction and control  

·       Integrate language models (e.g., BERT, GPT variants) to improve contextual and semantic understanding for natural intonation

·       Develop rule-based and neural solutions for emotion/style control in synthesized speech

·       Build state-of-the-art acoustic models (e.g., Tacotron, FastSpeech, VITS) to map linguistic features to spectrograms or waveform parameters.  

·       Optimize neural vocoders (e.g., WaveNet, HiFi-GAN, MelGAN, LPCNet) for high-fidelity, real-time speech synthesis

·       Optimize inference latencies for both edge devices and cloud platforms

·       Enhance robustness through noise suppression, speaker adaptation, and multilingual/cross-language/cross -gender voice cloning

Education: Master in CS, AI, EE, Math, or related field. 

Required/preferred skills: 

·       2+ years of hands-on experience in TTS system development with deep expertise in both frontend and backend components

·       Proficiency in C/C++ and Python, with mastery of ML frameworks (PyTorch, TensorFlow, etc)

·       Some background in NLP techniques and/or speech signal processing is welcome

·       Knowledge on transformer-based language models for prosody prediction

·       Basic understanding of autoregressive / non-autoregressive acoustic models and neural vocoders

·       Experience in optimizing models via quantization, pruning, or knowledge distillation  

·       Experience with ONNX Runtime, TensorRT, or TorchScript, etc

·       Experience with zero-shot/one-shot/few-shot voice cloning or emotional TTS systems  

·       Skilled GPU/TPU cluster and grid user

·       Fluent English is a must-have

Cerence Inc. (Nasdaq: CRNC and www.cerence.com) is the global industry leader in creating unique, moving experiences for the automotive world. Spun out from Nuance in October 2019, Cerence is a new, independent company that has quickly gained traction as a leader in the automotive voice assistant space, working with all of the world’s leading automakers – from Ford and Fiat Chrysler to Daimler, Audi and BMW to Geely and SAIC – to transform how a car feels, responds and learns. Its track record is built on more than 20 years of industry experience and leadership and more than 500 million cars on the road today across more than 70 languages.  

As Cerence looks to the future and continues an ambitious growth agenda, we need someone to join the team and help build the future of voice and AI in cars. This is an exciting opportunity to join Cerence’s passionate, dedicated, global team and be a part of meaningful innovation in a rapidly growing industry. 

Cerence is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination on the basis of age, race, color, gender, gender identity, gender expression, sex, sex stereotyping, pregnancy, national origin, ancestry, religion, physical or mental disability, medical condition, marital status, citizenship status, sexual orientation, protected military or veteran status, genetic information and other protected classifications. Cerence Equal Employment Opportunity Policy Statement.

All prospective and current Employees need to remain vigilant when it comes to executing security policies in the workplace. This includes:

- Following workplace security protocols and training programs to familiarize with the ways to maintain a safe workplace.
- Following security procedures to report any suspicious activity.
- Having respect for corporate security procedures to allow those procedures to be effective.
- Adhering to company's compliance and regulations.
- Encouraging to follow a zero tolerance for workplace violence.

- Basic knowledge of information security and data privacy requirements (e.g., how to protect data & how to be handling this data).

- Demonstrative knowledge of information security through internal training programs.