AI Localization platform for translating videos to 130+ languages with lip-sync feature. Research team focused on advancing text-to-speech technology

Responsibilities:
• Research and develop automated systems to annotate raw audio data for TTS and related tasks.
• Conduct applied research to improve data filtration systems and related tasks (e.g., filter out noisy recordings, music in background, or incorrect text annotations) using open-source models.
• Work with large-scale datasets and optimize the data processing pipeline for efficient storage and processing.
• Build, maintain, and optimize a feature storage system to compute, store, and stream enriched audio data features for TTS model training.

Requirements:
• 3+ years of experience as Data Engineer / ML Engineer
• Proficiency in Python, PyTorch
• Knowledge of statistics
• Experience with Docker, containers, remote servers 

Optional:
• Cloud platforms (AWS, Azure, GCP)
• Model serving tools (TorchServe / Triton Inference Server).
• SQL / NoSQL

Contacts:
📧 a.gribul@brask.ai