DSP Software Engineer
Listed on 2026-02-06
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Software Development
Software Engineer, Embedded Software Engineer, AI 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.
We build high-definition, multichannel audio experiences that set industry standards. Our products stream all the music on earth, throughout the home, wirelessly-and your work will help ensure the system remains simple, elegant, and robust.
Location: Boston, MA or Seattle, WA
Role OverviewOur mission is to advance the Sonos audio pipeline through bold innovation in DSP, machine learning, and embedded systems, creating seamless sound experiences that power Sonos' role as the essential platform for home entertainment. Working in close partnership with the Sound Experience, Trueplay and Headphone DSP teams, we design and deliver algorithms across audio, voice, and sensor domains-spanning both traditional DSP and cutting edge machine learning.
As an DSP Software Engineer on the Player DSP team, you'll contribute to the audio processing, DSP, and rendering software that powers every Sonos product. You will work across lowlevel embedded systems, realtime signal processing, and audio platform architecture to deliver high performance audio experiences.
This role is ideal for an early career engineer (IC1/IC2) who is passionate about audio, DSP, embedded systems, and developing reliable, well structured software. You should be comfortable working in Rust and C, eager to learn, and excited to develop features that directly impact how millions of listeners experience sound.
What You'll Do- Implement, extend, and maintain modular realtime audio and DSP components in Rust and
C. - Contribute to integrating and optimizing machine learning models for audio, including classification, enhancement, or spatial processing workloads on embedded platforms.
- Collaborate on the design of hard realtime software architectures for audio pipelines.
- Help integrate new multichannel audio formats, codecs, and DSP algorithms into Sonos platforms.
- Work with senior engineers to solve audio routing, timing, and synchronization challenges across wireless networks.
- Develop unit tests using GTest or Rust testing frameworks and contribute to continuous integration.
- Debug complex issues that may span DSP algorithms, embedded RTOS/Linux systems, wireless audio transport, or hardware interactions.
- Implement and document clean, maintainable, portable software that can run across processors and operating environments.
- Exposure to or interest in machine learning for audio (e.g., model inference on embedded systems, audio feature extraction, basic ML/DSP hybrid techniques).
- 0-3 years of experience in embedded software, DSP, or systems programming (industry, academic, or project-based experience).
- Proficiency in Rust and C programming.
- Foundational understanding of digital signal processing concepts (filtering, sampling, latency, numeric representation, etc.).
- Exposure to realtime systems, embedded Linux, or RTOS environments.
- Familiarity with multichannel audio concepts, streaming formats, or codecs (e.g., AAC, FLAC, Opus, Atmos) is a plus.
- Ability to write unit tests and design for testability.
- Strong problem solving skills and willingness to work handson at all layers of the audio stack.
- Interest in audio technology, DSP, music, or consumer hardware.
- Experience implementing or deploying machine learning models for audio (e.g., noise suppression, beamforming, sound classification, spatial audio ML techniques).
- Experience with performance benchmarking on embedded hardware.
- Coursework or project experience in wireless networking, timing, or synchronization.
- Exposure to source control and issue-tracking systems (e.g., Git, Jira, Perforce).
- Experience with performance benchmarking on embedded hardware.
- Coursework or project experience in wireless networking, timing, or synchronization.
- Exposure to source control and issue tracking systems (e.g., Git, Jira, Perforce).
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