Work in the Audio Machine Learning team of Sonos Voice Control
Design and train state-of-the-art machine learning models for automatic speech recognition and wakeword detection
Ensure our models perform the best they can on specialised domains, such as music entities, loudspeaker control and home automation
Define and implement the data strategy for training and testing, as well as audio augmentation to reflect the far-field acoustic conditions of our products
Maintain and improve scalable and efficient training and evaluation pipelines
Contribute to the team’s roadmap and set the technical direction for the ASR domain
Mentor other team members on ML best practices, experiment planning, and model analysis
Collaborate with the cloud backend and embedded engineering teams to ensure our models perform the best they can in the different environments

8+ years experience in machine learning research & engineering for voice applications
A PhD or Master’s degree in computer science, or a related technical field (or equivalent experience)
In-depth knowledge of speech processing (ASR, wakeword detection, audio features)
Experience in owning the whole model development lifecycle from data generation, training, evaluation to shipping models for production
Advanced knowledge of Python and common machine learning toolkits (PyTorch)
Intermediate knowledge of a low-level compiled language (Rust, C, C++)

Senior Machine Learning Engineer

Key skills