Senior Audio AI Engineer

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

Audio ML Development

• 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

Model Optimization & Deployment

• 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

Startup Innovation

• 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

Audio & ML Expertise

• 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

Model Optimization

• 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