Research and develop real-time AI audio-understanding algorithms for physical devices, including sound event detection, localization, acoustic scene analysis, anomaly detection, and multimodal sensor fusion. Build datasets, evaluation protocols, and prototypes; optimize models for accuracy, latency, and compute cost; collaborate with DSP and software engineers on product integration; and contribute to patents or conference publications.
At Bose Corporation, we believe sound is the most powerful force on earth - and for over 60 years, we have been a company built on innovation, excellence, and independence. Privately owned, fiercely customer-focused, and driven by our values, we continue to lead industries and transform lives through sound.
Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation.
Job Description
Description
The goal of our team is to develop novel AI-powered audio processing algorithms. The twist is that our algorithms must run in real time, on physical devices for applications such as context understanding, dynamic awareness, augmented hearing and ones we haven't yet imagined. You will work with experts in ML, DSP, software engineering, and psychoacoustics to prototype and implement new algorithms.
You will develop audio understanding algorithms that enable devices to recognize what is happening in the world around them. Areas of interest include sound event detection and localization (SELD), acoustic scene understanding, unusual or anomalous sound detection, and multimodal context understanding from audio, video, and motion sensors.
Bose has a strong history of combining creative thinking with cutting-edge audio technology. We are looking for people passionate about machine learning and audio to help shape what comes next.
Responsibilities
• 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 that combine microphone signals with video, IMU, or other sensor data when useful.
• Build and curate datasets and data piplines, evaluation protocols, and demonstrations that measure 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.
Education
Graduate degree (MS or PhD) in machine learning, computer science, electrical engineering, or a related field, or equivalent research experience.
Skills
• Strong hands-on experience with modern audio understanding models, including sound event detection, SELD, acoustic scene analysis, or anomaly detection.
• Comfortable tackling complex, open-ended problems where you have to experiment with and discard many ideas before finding the right solution.
• 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.
• Experience with multimodal fusion (video, IMU, or other sensors) for context understanding 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.
At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Framingham, Massachusetts is: $165,400-$227,500.The hiring range for other Bose work locations may vary. In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company-driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we're creating what's next-pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Let's Make Waves.
Today, Bose Corporation is entering an exciting new era. Across multiple global Business Units and Global Functions, we are shaping the future of audio technology, automotive, luxury, and premium experiences. We invite you to join us in this transformation.
Job Description
Description
The goal of our team is to develop novel AI-powered audio processing algorithms. The twist is that our algorithms must run in real time, on physical devices for applications such as context understanding, dynamic awareness, augmented hearing and ones we haven't yet imagined. You will work with experts in ML, DSP, software engineering, and psychoacoustics to prototype and implement new algorithms.
You will develop audio understanding algorithms that enable devices to recognize what is happening in the world around them. Areas of interest include sound event detection and localization (SELD), acoustic scene understanding, unusual or anomalous sound detection, and multimodal context understanding from audio, video, and motion sensors.
Bose has a strong history of combining creative thinking with cutting-edge audio technology. We are looking for people passionate about machine learning and audio to help shape what comes next.
Responsibilities
• 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 that combine microphone signals with video, IMU, or other sensor data when useful.
• Build and curate datasets and data piplines, evaluation protocols, and demonstrations that measure 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.
Education
Graduate degree (MS or PhD) in machine learning, computer science, electrical engineering, or a related field, or equivalent research experience.
Skills
• Strong hands-on experience with modern audio understanding models, including sound event detection, SELD, acoustic scene analysis, or anomaly detection.
• Comfortable tackling complex, open-ended problems where you have to experiment with and discard many ideas before finding the right solution.
• 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.
• Experience with multimodal fusion (video, IMU, or other sensors) for context understanding 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.
At Bose, you're inspired to be and do your best and are rewarded for your unique talents! Our compensation is thoughtfully tailored to your skills, experience, education, and location, and goes beyond base salary. The hiring range for this position in the primary work location of Framingham, Massachusetts is: $165,400-$227,500.The hiring range for other Bose work locations may vary. In addition to competitive base pay we offer rewards including bonus programs, comprehensive health and welfare benefits, a 401(k) plan, plus exclusive perks designed to support your wellbeing, and a generous employee discount where you can immerse yourself in our products and experiences. We are a proudly independent company-driven by purpose, guided by our values, and united by a belief in the power of sound. As the world leader in audio experiences, we're creating what's next-pushing boundaries and delivering transformative sound experiences for people everywhere. Join us and make your next career move a mic-drop. Let's Make Waves.
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Develop agentic workflows and automation for real-time audio machine learning research. Responsibilities include orchestrating data preparation, training, evaluation, hyperparameter searches, benchmarking, regression testing, experiment tracking, artifact management, GPU scheduling, and reproducible execution. The role connects LLM agents with research tools and infrastructure, builds dashboards and reports, and partners with audio researchers. Requires strong Python and software engineering skills, ML pipeline experience, PyTorch, Linux GPU operations, CUDA, containers, and audio ML/DSP knowledge.
Top Skills:
Ci/CdContainersCudaDigital Signal Processing (Dsp)Experiment TrackingGpu SchedulingLinuxLlm AgentsMlopsPythonPyTorch
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
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- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
