Principal Speech Data Linguist

InnoData

. Own the linguistic foundation of Innodata's segmentation and transcription work across languages, domains, and use cases .

Posted 9/24/2026full-timeRemote • United StatesLead💰 $160,000 - $185,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in transcription and segmentation standards, quality frameworks, and phonetic analysis, with a strong focus on multilingual and accented speech. Capable of training and mentoring teams while collaborating with research scientists to enhance ASR and TTS models.

Highest-signal resume keywords

Transcription StandardsPhonetic AnalysisAudio SegmentationPython ScriptingMultilingual Capability

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

TranscriptionSegmentationPhoneticsPhonologySociolinguisticsAcoustic AnalysisTimestampingDiarizationRegular ExpressionsData Management

Soft Skills

Strong CommunicationMentoringCollaboration

Tools & Technologies

WhisperAssemblyAIDeepgramRevSpeechmaticsMontreal Forced AlignerELAN

Industry Keywords

Quality FrameworksError TaxonomiesInter-Annotator AgreementHuman QAResponsible AI

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Own the linguistic foundation of Innodata's segmentation and transcription work across languages, domains, and use cases
Define transcription and segmentation standards, style guides, and annotation conventions
Establish and run quality frameworks, including rubrics, error taxonomies, adjudication processes, inter-annotator agreement, and human QA at scale
Own the end-to-end quality lifecycle for transcription and segmentation deliverables
Design human-in-the-loop workflows for review, correction, and adjudication as ASR quality improves
Handle difficult cases including accented and dialectal speech, low-resource and multilingual audio, overlapping speech, domain jargon, and noisy acoustic conditions
Partner with the Speech & Audio Research Scientist to translate model objectives into specifications and assess how transcription methods affect ASR, TTS, and speech/content-understanding models
Train, calibrate, and mentor expert transcribers and reviewers
Represent Innodata's transcription and segmentation approach to customers and frontier labs
Contribute to methodology and best-practice documentation

Requirements

What you’ll need

Substantial industry experience (typically 8+ years) in transcription, segmentation, and speech-data quality
Bachelor's degree in linguistics, phonetics, computational linguistics, or a closely related field is required
Strong foundation in phonetics, phonology, and sociolinguistics
Big-picture grasp of how transcription and segmentation choices affect speech and content-understanding models
Fluency in phonetic transcription and IPA
Hands-on experience with acoustic and phonetic analysis, including spectrograms, formants, pitch, prosody, and segment boundaries
Deep experience with audio segmentation, utterance and turn boundaries, timestamping, speaker labeling, and diarization
Hands-on fluency with Whisper, commercial ASR engines such as AssemblyAI, Deepgram, Rev, and Speechmatics, Montreal Forced Aligner, and ELAN
Python scripting for batch processing, QA, and metrics such as inter-annotator agreement and WER
Regular expressions and Praat scripting
Practical data-management skills across preprocessing, quality checks, post-processing, validation, and report packaging
Multilingual capability and hands-on experience with accented, dialectal, and code-switched speech
Strong written and verbal communication
Comfortable working with research scientists and customers
Bonus: responsible-AI considerations for speech, including accent and dialect bias, privacy, and consent in voice data