ML Engineer – Speech-to-Speech, Subject Matter Expert

Role Overview

• Provide expert-level advice and mentorship on the architecture, training, and production of text-to-speech (TTS) models
• Guide the implementation of robust testing methodologies for TTS models using industry standards like MOS testing
• Share expertise in distributed training, monitoring, and deployment of large-scale ML models on cloud platforms
• Lead latency optimization initiatives in real-time systems for high-quality speech-to-speech conversion
• Provide guidance on tuning TTS models for precise control over speech characteristics
• Share in-depth knowledge of various TTS model architectures and waveform generation methods
• Mentor the team on implementing advanced deep learning models for audio processing
• Guide the development of transformer architectures for complex TTS model development

Requirements

• 5+ years of proven experience in machine learning development focused on audio generation and TTS systems
• Extensive expertise in audio signal processing, particularly for human voices
• Deep experience with TTS models, including waveform generation and spectrogram-based methods
• Proven expertise in tuning TTS models for duration control and speech characteristics
• Strong proficiency in Python and machine learning frameworks such as PyTorch
• Experience with advanced deep learning models like WaveNet and transformer-based architectures
• Demonstrated experience in distributed training and deployment of ML models on cloud platforms
• Strong understanding of evaluation metrics for TTS systems
• Proven ability to provide technical leadership and actionable guidance
• Excellent communication and mentoring skills.

Tech Stack

• Cloud
• Python
• PyTorch

Benefits

• Engage directly with senior management and strategic advisory board members
• Gain valuable experience in the bleeding-edge AI space
• Remote-first culture with flexible working arrangements