Audio AI Research Scientist – Audio Source Separation

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🌐 United States, Italy, +9 more countries – Remote

🇺🇸 United States – Remote 🇮🇹 Italy – Remote 🇳🇴 Norway – Remote 🇦🇺 Australia – Remote 🇫🇷 France – Remote 🇩🇰 Denmark – Remote 🇵🇹 Portugal – Remote 🇨🇭 Switzerland – Remote 🇸🇪 Sweden – Remote 🇬🇧 United Kingdom – Remote 🇩🇪 Germany – Remote

🍂 Massachusetts – Remote

🍂 Massachusetts – Remote

💵 $165.4k - $227.5k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧠 AI Research Scientist

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Bose Corporation

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<Bose Corporation> is a global audio equipment company that designs, manufactures, and sells consumer and professional sound products, including headphones, earbuds, speakers, home theater systems, portable PA systems, and aviation headsets. The company operates direct-to-consumer online retail, offers protection plans and trade-in programs, and provides support services like repairs and corporate gifting. Bose emphasizes premium audio performance, noise-cancellation technology, and lifestyle-oriented marketing.

📋 Description

• Research, prototype, train, and evaluate novel source separation and extraction algorithms for speech and other real-world sounds • Develop approaches for single- and multi-microphone recordings, including spatial cues and optional auxiliary sensors • Investigate robust separation in overlapping talkers, noise, reverberation, and motion • Evaluate perceptual quality, separation performance, generalization, latency, memory, and computational requirements • Collaborate with DSP and embedded software teams to deploy models in real-time demonstrations and product platforms • Contribute to patents and conference papers • Develop next-generation algorithms that isolate, extract, or suppress individual sound sources from microphone recordings for real-time physical-device applications

🎯 Requirements

• Graduate degree (MS or PhD) in machine learning, electrical engineering, computer science, or a related field, or equivalent research experience • Deep hands-on experience in audio source separation, target sound extraction, speech enhancement, or related neural audio processing • Strong knowledge of audio DSP, time-frequency methods, and microphone array or spatial signal processing • Experience training and evaluating audio models in PyTorch • Proficiency in Python • Understanding of objective and perceptual evaluation methods and real-time low-power inference tradeoffs • Comfortable tackling complex, open-ended problems requiring experimentation • Familiarity with C/C++ is a plus • Experience with multimodal or sensor-conditioned separation, ONNX/TFLite, or embedded deployment is a plus • Strong communication skills • Publications at conferences such as ICASSP, Interspeech, NeurIPS, or similar are welcome but not required

🏖️ Benefits

• Bonus programs • Comprehensive health and welfare benefits • 401(k) plan • Exclusive perks designed to support wellbeing • Generous employee discount • Compensation beyond base salary

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