TTS Research Engineer (AI)

TL;DR

TTS Research Engineer (AI): Designing and optimizing advanced text-to-speech and NLP preprocessing pipelines for automotive voice assistants with an accent on deep learning acoustic models and neural vocoders. Focus on enhancing real-time synthesis performance for edge and cloud deployment while integrating state-of-the-art language models for expressive, natural voice cloning.

Company

A global leader in automotive voice assistant technology and AI-powered in-car experiences with over 20 years of industry expertise.

What you will do

• Design and optimize text/NLP preprocessing pipelines including G2P conversion and prosody prediction.
• Develop and implement neural solutions for emotion and style control in speech synthesis.
• Build and refine state-of-the-art acoustic models (e.g., VITS, FastSpeech) to improve synthesis quality.
• Optimize neural vocoders for high-fidelity, real-time speech synthesis performance.
• Improve system robustness through speaker adaptation, noise suppression, and multilingual voice cloning.
• Optimize inference latencies for diverse automotive edge and cloud platforms.

Requirements

• Master's degree in Computer Science, AI, EE, Math, or a related field.
• 2+ years of hands-on experience in TTS system development covering both frontend and backend.
• Proficiency in C++ and Python with deep expertise in PyTorch or TensorFlow.
• Knowledge of transformer-based language models for prosody control.
• Experience with quantization, pruning, or knowledge distillation for model optimization.
• Fluent English is a mandatory requirement.

Nice to have

• Familiarity with ONNX Runtime, TensorRT, or TorchScript.
• Background in speech signal processing or NLP techniques.
• Experience with zero-shot/few-shot voice cloning systems.
• Proficiency in utilizing GPU/TPU cluster and grid environments.

Culture & Benefits

• Opportunity to innovate in a rapidly growing industry with a passionate global team.
• Work on meaningful technology integrated into hundreds of millions of vehicles worldwide.
• Exposure to a collaborative environment working with leading global automakers.
• Commitment to Equal Employment Opportunity and high standards of workplace security and safety.