Machine Learning Engineer

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. The current role has a strong focus on the optimization and shipping machine learning inference, but also contributes to the other stages of the model development lifecycle.

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

• Bring our state-of-the-art machine learning models to production by maintaining and implementing libraries for on-device and cloud inference

• Ensure our models run efficiently and fast on various types of hardware by applying optimization on low-level operations of the inference code

• Benchmark models during development to allow the team to make informed decisions on model architectures and new approaches

• 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

• 4+ years experience in software engineering, particularly writing and maintaining efficient production-ready codebases, unit/integration testing, deploying to production systems

• Advanced knowledge of at least one high-performance compiled language (e.g. Rust, C, C++)

• 1-2+ years experience working on machine learning

• Intermediate knowledge of Python and latest ML libraries (e.g. PyTorch)

• A Master’s degree in computer science, or a related technical field (or equivalent experience)

Preferred Skills

• Experience in model inference for real-time, production-grade ML systems

• Experience with low-level optimization on CPU and GPU (Cuda, SIMD, etc.)

• Experience with audio processing (e.g. ASR, speech enhancement, audio classification) and latest trends in streaming ASR (transducer architectures)

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.

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