Senior Applied ML Engineer (Speech Audio)

Role overview

Responsibilities

• check_circle Benchmark TTS and ASR models on Arabic datasets (WER, naturalness, dialect coverage)
• check_circle Fine-tune generative architectures for voice cloning and zero-shot speaker adaptation
• check_circle Build and maintain Arabic-specific audio data pipelines
• check_circle Optimize production inference for low latency
• check_circle Integrate and evaluate full-stack speech-to-speech pipelines

Basic qualifications

• 5+ years of experience in Machine Learning / AI Research
• Strong Python, PyTorch & Hugging Face skills
• Hands-on experience with TTS, ASR or Audio Codec models
• Strong understanding of speech architectures such as Whisper, Conformer, HiFi-GAN or Diffusion
• Experience with VAD, speaker diarization and neural vocoders
• Ability to turn research papers into production-ready experiments
• Knowledge of Arabic NLP, including diacritization (Tashkil) and dialect variations
• Experience with inference optimization: quantization, streaming, TensorRT, etc.

Preferred qualifications

• Experience with high-performance CUDA kernels
• Experience with speculative decoding

Benefits

• check_circle Pay: 10,000.00DH - 20,000.00DH per month
• check_circle Work Location: Hybrid remote in Casablanca