Job opportunity
Senior Audio AI Engineer
Waveshaper Technologies Inc.
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 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
#J-18808-Ljbffr
Apply on source site 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 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
#J-18808-Ljbffr