Live opening · Posted 2 days ago
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About the role
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About The Opportunity
A fast-scaling AI-first startup in the speech technology and conversational AI sector, we build next-gen transcription engines that power voice assistants, call centers, and accessibility tools across global markets. Our team focuses on reducing Word Error Rate (WER) through data science, acoustic modeling, and linguistic refinement — enabling near-human accuracy for multilingual, noisy, and domain-specific speech.
Role & Responsibilities
Optimize ASR pipelines to reduce WER across noisy, accented, and domain-specific audio (call center, medical, legal).
Analyze transcription errors and recommend targeted data, feature, or model improvements to boost accuracy.
Curate, label, and augment speech datasets — balancing coverage, diversity, and domain relevance.
Run AB tests on model variants, measure WER impact, and document performance trade-offs.
Collaborate with ML engineers to integrate WER feedback loops into training and inference workflows.
Define and automate WER evaluation benchmarks for continuous model improvement.
Skills & Qualifications
Must-Have
WER analysis
ASR systems
Speech dataset curation
Python
Speech preprocessing
Acoustic modeling basics
AB testing
Kaldi or Whisper
Preferred
Experience with Hugging Face Transformers
Kaldi pipelines
Punctuation restoration
Benefits & Culture Highlights
100% remote with flexible hours — work from anywhere in India
Impact-driven culture — your optimizations directly improve real-world ASR performance
Access to the latest speech AI tools and research — stay at the bleeding edge
Skills: data,acoustic modeling,access,modeling,speech,pipelines,python,transcription,accessibility,acoustic
Work arrangement
Yes
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