Expertise Audio & MLEsprit Startup_____________About Waveshaper AIWaveshaper 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 RoleWe'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 setting.Key Responsibilities:Design and train neural audio processing models for noise reduction, speech enhancement, and quality improvementEvaluate audio quality using both
subjective listening
and
objective metricsBuild scalable ML pipelines and audio data strategiesDevelop model architectures optimized for real-time audio applicationsImplement model compression, quantization, and pruning techniquesOptimize ML models for edge devices with
memory and latency constraintsDeploy models across diverse platforms and hardware configurationsBuild MLOps pipelines for training, versioning,
and automated deploymentMake technical decisions with incomplete information and iterate rapidlyWork directly with customers to validate solutions and gather feedbackBalance technical excellence with product delivery timelinesTranslate audio AI breakthroughs into market-ready featuresQualifications :5+ years
audio signal processing and ML model developmentDeep understanding of
audio quality metrics
and
perceptual audio processingExperience with
neural network architectures
for audio applicationsProficiency with
TensorFlow ,
PyTorch, and audio ML frameworks3+ years
experience with model compression and edge deploymentKnowledge of
quantization ,
pruning, and
distillation
techniquesUnderstanding of
resource-constrained optimizationExperience with
MLOps
and production ML systemsStartup MindsetEntrepreneurial drive
to move fast and adapt quicklyExperience with cloud platforms (GCP/AWS) and ML infrastructureStrong
Python
programming and data engineering skillsAbility to work in fast-paced, evolving environmentsPreferred Qualifications:Degree in Computer Science, Engineering, or related fieldAudio industry or real-time audio systems experienceExperience with edge ML frameworks (TensorFlow Lite, ONNX)Startup environment experienceWhat We Offer:Technical ownership
of cutting-edge audio AI technologyTechnical autonomy
and direct product impactCompetitive package
in Montreal (remote options available)Ready to revolutionize audio AI?
Join us in building intelligent audio processing for edge devices
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