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AI Voice Biometric Liveness Detection Developer

Brandon Kim

Full-time · Job · New_York

About the role

Voice biometrics verify identity by matching a speaker's voice against an enrolled voiceprint. The problem: a recording of someone's voice can fool a basic system, and AI-generated deepfake voices are getting good enough to fool advanced ones. Liveness detection — proving that the voice is coming from a real, present human rather than a recording or synthesis — is the last line of defense. You'll build liveness detection models that distinguish live speech from replay attacks, voice cloning, and text-to-speech synthesis. The detection must work across different phone types, network conditions, and environmental noise levels without adding friction to the authentication experience. A false rejection means a legitimate user gets locked out; a false acceptance means a fraudster gets in. The voice security team is five engineers. You'll be the senior engineer who drives the liveness detection architecture, working alongside the voiceprint matching team and the anti-fraud team who track emerging attack techniques.

Responsibilities

  • Build liveness detection distinguishing live speech from replay and synthesis attacks
  • Design robustness testing against AI-generated deepfake voices
  • Handle diverse conditions: phone types, network quality, environmental noise
  • Calibrate detection thresholds balancing security against user friction
  • Track and adapt to emerging voice spoofing techniques
  • Evaluate liveness detection against adversarial attack datasets

Requirements

  • 5+ years in speech or audio ML with security or biometric focus
  • Experience with speaker verification, anti-spoofing, or liveness detection
  • Strong PyTorch skills for audio model development
  • Understanding of adversarial attacks and robustness testing
  • Knowledge of biometric security standards and evaluation protocols

Benefits

  • Fully remote with flexible schedule
  • Competitive salary plus equity
  • Comprehensive health coverage
  • $4,000 annual conference budget
  • Protect voice authentication for millions of users

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Categories

AI & Machine Learning Engineers AI Product & Strategy

Skills

python pytorch docker aws statistics

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

AI & Machine Learning Engineers AI Product & Strategy

Skills

python pytorch docker aws statistics

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