At Awarri, our mission is to enable the development and adoption of frontier technology across Africa, starting in Nigeria. We are building inclusive AI technologies—from LLMs to speech models—that reflect and empower African languages and cultural contexts.
Why Join Awarri?
Be part of a pioneering initiative shaping the future of AI in Africa.
Work on impactful projects that center real-world representation and inclusivity.
Collaborate with a passionate, globally distributed team of engineers, linguists, and researchers.
As a Senior Audio AI Engineer at Awarri, you will play a pivotal role in advancing the naturalness and quality of our Text-to-Speech (TTS) systems, focused on African languages and accents. We're seeking an engineer who understands the intricacies of prosody, rhythm, and speech alignment—and is excited to push the boundaries of audio AI in a meaningful cultural context.
This role is best suited for a specialist with deep experience in speech technologies and a passion for building expressive, production-ready TTS models. You’ll be joining a collaborative, mission-driven team dedicated to shaping the future of generative audio systems in Africa.
Responsibilities
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
.
Your Experience
Technical Expertise:
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).
Linguistic & Cultural Sensitivity:
Experience working with multilingual or low-resource speech data.
Familiarity with phonetics/phonology, especially as it relates to prosody and rhythm.
Engineering Workflow:
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.
Nice to Have
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.