Senior Audio AI Engineer – TTS / Speech Synthesis

Model Development & Fine-Tuning

• →Optimize neural TTS models for prosody, pacing, and expressiveness (e.g., Tacotron 2, FastSpeech 2, Glow-TTS, VITS).
  
• →Improve duration prediction and phoneme-to-frame alignment using forced aligners or prosody-aware training.
  
• →Incorporate punctuation and linguistic markers into the model pipeline to improve natural flow.
  
• →Implement and fine-tune transformer-based architectures for speech synthesis and text-to-speech tasks.
  
  

Audio Engineering & Vocoder Optimization

• →Evaluate and fine-tune neural vocoders (e.g., HiFi-GAN, WaveGlow) to match desired voice characteristics and audio quality.
  
• →Identify and correct audio artifacts or inconsistencies in generated speech.
  
• →Optimize speech processing pipelines for efficiency and real-time performance.
  
  

Evaluation & Iteration

• →Lead both objective (e.g., duration errors, pitch contours) and subjective (e.g., MOS scoring) evaluations of TTS quality.
  
• →Collaborate with linguistic teams to benchmark pronunciation accuracy in Nigerian languages.
  
• →Develop automated testing frameworks to validate speech synthesis quality at scale.
  
  

Deployment & Production Readiness

• →Prepare the TTS system for product integration by improving inference speed and robustness.
  
• →Support the deployment of models across various platforms (cloud, mobile, embedded).
  
• →Optimize model inference using VLLM for efficient deployment.
  
• →Build APIs and backend services for TTS deployment using FastAPI and Flask.
  
• →Implement and manage data pipelines and storage solutions using MongoDB and MySQL.
  
  

Technical Skills & Requirements

• →Proficiency in Python and TypeScript for model development and backend integration.
  
• →Experience with transformer-based models for speech synthesis and NLP.
  
• →Strong background in machine learning frameworks such as TensorFlow or PyTorch.
  
• →Experience in designing scalable AI-driven applications.
  
• →Familiarity with FastAPI, Flask, and cloud-based deployment environments.
  
• →Knowledge of database management using MongoDB and MySQL.

• 3+ years of experience developing and deploying TTS or speech generation systems (bonus for low-resource languages)
  
• Deep knowledge of at least one neural TTS architecture and related vocoders.
  
• Proficiency with PyTorch, TensorFlow, or JAX for building and training models.
  
• Experience with audio processing tools (e.g., librosa, Praat, torchaudio).
  
  

• Experience working with multilingual or low-resource speech data.
  
• Familiarity with phonetics/phonology, especially as it relates to prosody and rhythm.
  
  

• Experience building scalable training and evaluation pipelines.
  
• Ability to debug complex model behavior and iterate quickly toward product quality.
  
• Comfort working remotely and asynchronously with interdisciplinary teams.
  
  

• Prior work on African language speech systems or expressive TTS in non-English languages.
  
• Interest in linguistic or cultural technology in the African context.
  
• Contributions to open-source TTS or audio AI tools.
  
• Experience with emotion modeling or speaker adaptation.