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AI Real-Time Speech Enhancement Developer

Brandon Kim

Full-time · Job · Los_Angeles

About the role

Our voice agents operate in call centers, retail environments, and healthcare settings where background noise, acoustic reflections, and overlapping speech are constant. When the ASR system mishears a command because of ambient noise, the downstream NLU gets garbage input and the interaction fails. Speech enhancement — cleaning the audio signal before ASR — is a low-level fix with system-level impact. We need a real-time neural speech enhancement system with sub-20ms latency that suppresses broadband noise, removes reverberation, and handles overlapping talker scenarios without introducing audible artifacts. The system runs on commodity cloud hardware — no specialized DSPs — and must handle all major deployment environments: phone calls, WebRTC streams, and direct microphone capture. You'll design and train the enhancement model, optimize it for real-time streaming inference, and validate performance across the acoustic environments our clients actually deploy in. You'll work closely with the ASR team to measure whether enhancement improvements translate to downstream word error rate reductions.

Responsibilities

  • Design and train neural speech enhancement models for noise suppression and dereverberation
  • Optimize for real-time streaming inference with sub-20ms processing latency
  • Handle overlapping speech and concurrent talker scenarios
  • Validate performance across phone, WebRTC, and direct microphone environments
  • Measure impact on downstream ASR word error rate as primary quality signal
  • Build evaluation benchmarks from real deployment acoustic environments

Requirements

  • 3+ years in audio ML, speech enhancement, or signal processing
  • Experience with neural noise suppression, beamforming, or dereverberation systems
  • Strong PyTorch skills and real-time audio processing knowledge
  • Understanding of streaming inference constraints and latency budgets
  • Familiarity with speech quality metrics: PESQ, STOI, MOS

Benefits

  • Fully remote
  • Health and dental
  • $3,000 annual learning budget
  • 401(k) with match
  • Stock options

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Categories

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch docker aws fastapi

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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 docker aws fastapi statistics

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