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AI Speech Recognition Engineer

Nelvix Labs

Hybrid · $100k – $130k / year · Full-time · Posted 4 months ago

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About the role

Court reporters transcribe legal proceedings at 225 words per minute with 98.5% accuracy. Our AI does it at infinite words per minute with 95% accuracy. That gap — 95% to 98.5% — is where you come in. Closing it means understanding legal terminology, courtroom acoustics, multiple simultaneous speakers, and the specific cadences of judges, attorneys, and witnesses. You'll work on our domain-specific ASR models: fine-tuning Whisper and custom encoder-decoder architectures on thousands of hours of courtroom audio. You'll also build the post-processing pipeline — punctuation restoration, speaker attribution, and legal citation formatting. Hybrid role with 2 days/week in our NYC office, where we have a dedicated audio lab for testing with real courtroom recording equipment.

Responsibilities

  • Fine-tune ASR models on domain-specific legal and courtroom audio
  • Build post-processing pipelines for punctuation, speaker attribution, and formatting
  • Design evaluation frameworks measuring accuracy on legal terminology
  • Optimize inference for real-time transcription during live proceedings
  • Test models with courtroom recording equipment in the audio lab

Requirements

  • 3+ years in speech recognition or audio ML
  • Strong PyTorch experience with encoder-decoder architectures
  • Familiarity with Whisper, wav2vec, or similar ASR frameworks
  • Understanding of audio preprocessing and feature extraction
  • Willingness to work hybrid (2 days/week in NYC)

Benefits

  • Hybrid — NYC office 2 days/week with dedicated audio lab
  • Competitive salary with equity
  • Health and dental insurance
  • $2,500 conference and learning budget

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Categories

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch tensorflow docker aws sql

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