At Sonos we want to create the ultimate listening experience for our customers and know that it starts by listening to each other. As part of the Sonos team, you’ll collaborate with people of all styles, skill sets, and backgrounds to realize our vision while fostering a community where everyone feels included and empowered to do the best work of their lives.
This role is a hybrid position
This position is considered hybrid, allowing for a combination of remote work and in-office collaboration. Qualified applicants must live within commuting distance of our Paris office location and should expect to be in office approximately 3 days per week.
In the Sonos Voice Control team we design the future of AI based interactions to power music control and content discovery for Sonos customers on any control surfaces (Sonos hardware, Sonos Application, Sonos Voice Control).
We are seeking an experienced ML engineer to join the Audio Machine Learning team, focused on building the next generation of Sonos Voice Control. The team develops all audio-based components of Sonos' in-house voice assistant solution, including far-field automatic speech recognition (ASR), wakeword detection, and speech enhancement. The team is also in charge of shipping those models to production and running them efficiently and fast on multiple types of hardware.
What You’ll Do
Work in the Audio Machine Learning team of Sonos Voice Control, together with a group of experienced machine learning engineers and researchers
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
What You’ll Need
Basic Qualifications
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), particularly latest architectures for automatic speech recognition (RNN-T, Transformers)
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++)
Preferred Skills
Experience in developing models for real-time, low latency, streaming ASR
Experience in model adaptation techniques for large entity catalogs (shallow-fusion biasing, rescoring, error correction)
Understanding of the particular challenges of far-field ASR, including acoustics and data augmentation for model training and evaluation
MLOps and software engineering for efficient training and data infrastructure
Research shows that candidates from underrepresented backgrounds often don't apply for roles if they don't meet all the criteria. If you don’t have 100% of the skills listed, we strongly encourage you to apply if interested.
#LI-hybrid
Your profile will be reviewed and you'll hear from us once we have an update. At Sonos we take the time to hire right and appreciate your patience.
Skills Required
- 8+ years experience in machine learning research & engineering for voice applications
- A PhD or Master's degree in computer science or a related field
- In-depth knowledge of speech processing techniques such as ASR and wakeword detection
- Experience in the model development lifecycle from data generation to production
- Advanced knowledge of Python and machine learning toolkits (PyTorch)
- Intermediate knowledge of a low-level compiled language (Rust, C, C++)
Sonos Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Sonos and has not been reviewed or approved by Sonos.
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Healthcare Strength — Multiple medical plan options with in‑network preventive care covered and day‑one eligibility indicate comprehensive healthcare support. Wellness programs and access to mental‑health resources further reinforce depth of coverage.
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Parental & Family Support — Paid parental leave applies to both birthing and non‑birthing parents globally, with additional medical recovery time for birthing parents. This breadth positions family support as a clear strength of the package.
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Leave & Time Off Breadth — An open time off policy in the U.S. and company holidays provide flexible avenues for rest. Paid volunteer time adds further optionality for time away.
Sonos Insights
What We Do
We connect millions of listeners all around the world to the content they want, where and how they want it. Since inventing multiroom wireless audio in 2005, we have continuously innovated the listening experience, designing hardware and software that celebrates sound, empowers our customers, and brings the home to life. Our team is made up of passionate players united by a culture of respect, transparency, collaboration, and ownership who want to inspire the world to listen better.
Why Work With Us
Sonos is a global company that boasts a rich culture of diversity and innovation. With over 1,800 employees distributed across the world, we work remotely from home or an office location (when required). We value a diverse workforce that enables each employee to do the best work of their life and contribute to projects they are passionate about.
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