About Analog Devices
Analog Devices, Inc. (NASDAQ: ) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at and on and.
ML/AI Audio and Acoustics Software Engineer
Location
Belgium (Hybrid / Onsite)
Summary
We are looking for an experienced ML/AI Audio & Acoustics Engineer to contribute to the design and implementation of state-of-the-art deep learning models for very low latency audio and speech enhancement applications in ANC hearables. You will join a multidisciplinary team of ML scientists, acoustics engineers, and DSP software developers, working on technologies that improve audio capture, hearing enhancement, and rendering in real-world devices.
Responsibilities
1. Assist in developing, training, and evaluating deep learning models for tasks such as speech enhancement, noise suppression, source separation, dereverberation, and classification.
2. Contribute to data collection, dataset curation, pre-processing, and augmentation pipelines.
3. Prototype models in Python (PyTorch / TensorFlow), validate performance against acoustic datasets, and iterate with senior engineers.
4. Support model optimization for inference (quantization, pruning, compression) on embedded / mobile platforms.
5. Collaborate with acoustics engineers to understand physical constraints and integrate ML solutions with microphones, speakers, and arrays.
6. Contribute to lab measurements, test automation, and benchmarking of algorithms in controlled and real-world environments.
7. Document design choices, results, and learnings.
Minimum Qualifications
8. Master’s degree in Computer Science, Electrical Engineering, Acoustics, Applied Math, or equivalent.
9. Strong knowledge of deep learning and neural network architectures (CNNs, RNNs, Transformers) with application to audio/speech/hearing.
10. Good knowledge of speech enhancement and adaptive filtering DSP techniques.
11. Good knowledge and understanding about ANC.
12. Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Keras).
13. Basic knowledge of audio signal representation (STFT, mel spectrograms, waveforms).
14. Familiarity with both Windows and Linux development environments and version control (Git).
15. Strong problem-solving and willingness to learn in a multidisciplinary environment.
16. Start-up mindset.
Preferred Qualifications
17. Internship or thesis experience in audio ML (speech enhancement, separation, or classification).
18. Exposure to on-device ML (TinyML, edge inference, quantization).
19. Experience with data labeling, augmentation, or large-scale training pipelines.
20. Basic C/C++ skills for model integration.
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Job Req Type: ExperiencedRequired Travel: Yes, 10% of the timeShift Type: 1st Shift/Days