Expertise Audio & ML Esprit Startup _____________ 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 quick 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