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Audio AI Research Scientist – Audio Understanding
Bose Corporation. Research, prototype, train, and evaluate novel audio understanding models from early experiments through real-time deployment on devices .
Posted 11/3/2026full-timeRemote • Massachusetts • United States, Italy, Japan, Norway, Australia, France, Denmark, Portugal, Switzerland, Sweden, United Kingdom, GermanyMid-LevelSenior💰 $165,400 - $227,500 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and evaluating audio understanding models, including sound event detection and acoustic anomaly detection, while leveraging deep learning frameworks like PyTorch. Proficient in Python and experienced in multimodal data integration and evaluation metrics.
Highest-signal resume keywords
Audio Understanding ModelsDeep Learning Model DevelopmentPyTorchSound Event DetectionMultimodal Fusion
ATS Keywords
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Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Sound Event DetectionAcoustic Anomaly DetectionDeep LearningPythonDSPEvaluation MetricsMultimodal FusionCausal MLONNXTFLite
Soft Skills
Strong Communication SkillsProblem-Solving
Certifications & Qualifications
Graduate Degree (MS or PhD)
Industry Keywords
Machine LearningComputer ScienceElectrical EngineeringAudio RepresentationData PipelinesAccuracy MeasurementRobustness MeasurementLatency MeasurementCompute Cost MeasurementPublications
Tech Stack
Tools & technologiesPythonPyTorchC++
About the role
Key responsibilities & impact- Research, prototype, train, and evaluate novel audio understanding models from early experiments through real-time deployment on devices
- Develop robust methods for sound event detection/localization, acoustic anomaly detection, and context-aware audio interpretation
- Explore multimodal approaches combining microphone signals with video, IMU, or other sensor data
- Build and curate datasets and data pipelines, evaluation protocols, and demonstrations measuring accuracy, robustness, latency, and compute cost
- Work with DSP and software engineers to integrate models into proof-of-concept systems and product platforms
- Communicate results and contribute to patents or conference papers
Requirements
What you’ll need- Graduate degree (MS or PhD) in machine learning, computer science, electrical engineering, or a related field, or equivalent research experience
- Strong hands-on experience with modern audio understanding models, including sound event detection, SELD, acoustic scene analysis, or anomaly detection
- Experience developing and evaluating deep learning models in PyTorch
- Strong Python skills
- Understanding of audio representations, DSP, and evaluation metrics for detection, localization, and generalization
- Comfortable tackling complex, open-ended problems requiring experimentation
- Experience with multimodal fusion using video, IMU, or other sensors is a plus
- Experience with efficient inference, causal ML, ONNX/TFLite, embedded ML, or C/C++ is a plus
- Strong communication skills
- Publications at conferences such as ICASSP, Interspeech, NeurIPS, or similar are welcome but not required
Benefits
Comp & perks- Bonus programs
- Comprehensive health and welfare benefits
- 401(k) plan
- Exclusive perks designed to support wellbeing
- Generous employee discount
- Compensation beyond base salary