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Niche speech specialization reduces applicants, but Series C metro startup and ML role attract moderate competition.
Specialized speech ASR expertise limits cross-industry transferability.
Tier-1 degree, 2+ years, and mandatory ASR production experience create high candidate filtering.
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Own the development, deployment, and maintenance of scalable automatic speech recognition (ASR) pipelines powering the company’s ASR engine.
Address core problems in speech-to-text pipelines including transcription, diarization, and voice activity detection using state-of-the-art ASR techniques.
Collaborate on architecture and system design, independently experiment with ASR model architectures and training methods in an agile environment.
At least 2 years of experience working on Deep Learning models for speech recognition pipelines.
Bachelor's degree in Computer Science or related field from a tier-1 engineering institute.
Proficiency in Python and PyTorch for model development and deployment.
Strong knowledge in Machine Learning fundamentals and awareness of SOTA research in speech recognition and signal processing.
Experienced in building and deploying large-scale machine learning applications focused on speech recognition.
Demonstrates ability to independently experiment with model architectures and training schemes from recent ASR literature.
Comfortable working in agile teams with peers from top technology companies, contributing to cutting-edge AI-driven enterprise solutions.