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AI Audio Fingerprint Matching Engineer

Victoria Nakamura

Full-time · Job · Los_Angeles

About the role

Our mission is to make sure independent musicians get paid every time their work is sampled, remixed, or reused. This role sits at the center of that mission: building audio fingerprinting models robust enough to detect a sample buried under pitch shifts, tempo changes, and layered production. The matches you ship determine whether an artist gets credited and compensated correctly.

Responsibilities

  • Train and evaluate audio fingerprinting models against real remixes
  • Improve robustness to pitch, tempo, and effects-chain distortion
  • Benchmark matching accuracy against our licensing team's ground truth
  • Optimize inference speed for our catalog-scale matching pipeline

Requirements

  • 5+ years working with audio ML or signal processing models
  • Strong PyTorch or TensorFlow experience at production scale
  • Understanding of audio feature extraction techniques
  • Comfortable working with large, noisy real-world audio catalogs

Benefits

  • Fully remote position
  • Competitive salary + equity
  • Health and dental insurance
  • Annual conference budget

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Categories

AI & Machine Learning Engineers

Skills

python tensorflow pytorch numpy

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Job Type

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Level

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Language

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Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers

Skills

python tensorflow pytorch numpy

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