Senior Audio AI Engineer

Waveshaper Technologies Inc.; Montreal (administrative region); On-site; CAD 120,000 - 180,000; Full time

Benefits offered by this job

Technical ownership of audio AI tech

Autonomy and direct product impact

Remote options available

Job summary

Waveshaper AI seeks a Senior Audio AI Engineer to develop neural audio models for edge deployment and real-time processing in a startup-focused environment.

You will design, train, and optimize architectures for noise reduction, speech enhancement, and audio quality improvements while collaborating with customers to validate solutions and drive market-ready features.

Qualifications

• 5+ years in audio signal processing and ML model development.
• Expertise in audio quality metrics and perceptual processing.
• Experience with neural network architectures for audio.

Responsibilities

• Design and train neural audio processing models for noise reduction, speech enhancement, and quality improvement.
• Evaluate audio quality using subjective listening and objective metrics.
• Build scalable ML pipelines and audio data strategies.
• Develop model architectures optimized for real-time audio applications.
• Implement model compression, quantization, and pruning techniques.
• Optimize ML models for edge devices with memory and latency constraints.
• Deploy models across diverse platforms and hardware configurations.
• Build MLOps pipelines for training, versioning, and automated deployment.
• Collaborate with customers to validate solutions and gather feedback.
• Balance technical excellence with product timelines.
• Translate audio AI breakthroughs into market-ready features.

Skills

Audio signal processing

ML model development

Python programming

Education

Degree in Computer Science or Engineering

Tools

TensorFlow

PyTorch

ONNX

MLOps

Job description

Expertise Audio & ML

Esprit Startup

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About Waveshaper AI

Waveshaper AI revolutionizes audio processing with edge-ready AI that brings studio-quality sound to any device. Our patented audio-to-audio learning technology powers ultra-lightweight neural models for real-time audio processing.

About the Role

We're seeking a Senior Audio AI Engineer with an entrepreneurial mindset to develop neural audio models for edge deployment. Drive breakthrough ML innovations while moving fast in a startup environment.

Key Responsibilities:

• Design and train neural audio processing models for noise reduction, speech enhancement, and quality improvement
• Evaluate audio quality using both subjective listening and objective metrics
• Build scalable ML pipelines and audio data strategies
• Develop model architectures optimized for real-time audio applications
• Implement model compression, quantization, and pruning techniques
• Optimize ML models for edge devices with memory and latency constraints
• Deploy models across diverse platforms and hardware configurations
• Build MLOps pipelines for training, versioning, and automated deployment
• Make technical decisions with incomplete information and iterate rapidly
• Work directly with customers to validate solutions and gather feedback
• Balance technical excellence with product delivery timelines
• Translate audio AI breakthroughs into market-ready features

Qualifications :

• 5+ years audio signal processing and ML model development
• Deep understanding of audio quality metrics and perceptual audio processing
• Experience with neural network architectures for audio applications
• Proficiency with TensorFlow, PyTorch, and audio ML frameworks
• 3+ years experience with model compression and edge deployment
• Knowledge of quantization, pruning, and distillation techniques
• Understanding of resource-constrained optimization
• Experience with MLOps and production ML systems

Startup Mindset

• Entrepreneurial drive to move fast and adapt quickly
• Experience with cloud platforms (GCP/AWS) and ML infrastructure
• Strong Python programming and data engineering skills
• Ability to work in fast-paced, evolving environments

Preferred Qualifications:

• Degree in Computer Science, Engineering, or related field
• Audio industry or real-time audio systems experience
• Experience with edge ML frameworks (TensorFlow Lite, ONNX)
• Startup environment experience

What We Offer:

• Technical ownership of cutting-edge audio AI technology
• Technical autonomy and direct product impact
• Competitive package in Montreal (remote options available)

Ready to revolutionize audio AI? Join us in building intelligent audio processing for edge devices