Develop, train, evaluate, optimize, and debug machine learning models for consumer audio applications. Focus on efficient AI and Edge ML by reducing latency, memory usage, and computational demands. Collaborate with software, embedded systems, and hardware engineers to deploy models on resource-constrained devices. Explore techniques such as quantization, pruning, and model compression while contributing to emerging AI technologies and practical product development.
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
Build AI that people can hear and experience.
At Bose, we believe sound is the most powerful force on earth. As a Machine Learning / AI Engineer, you'll help bring that belief to life - developing intelligent capabilities for the next generation of audio experiences.
If you enjoy experimenting with models, solving practical problems, and turning ideas into working technology, this is an opportunity to grow your skills while contributing to products and technology that people use every day.
About the Role
You'll help design, train, test, and optimize machine learning models, with a focus on making AI work efficiently on devices with limited memory and computing power. This work brings together Efficient AI and Edge ML: building models that deliver strong results within the constraints of real products.
You'll collaborate with engineers across machine learning, software, embedded systems, and hardware. Along the way, you'll deepen your technical expertise, contribute your ideas, and learn how models move from experimentation toward deployment.
What You'll Do
What You'll Bring
Experience That Can Help You Stand Out
You don't need experience in every area below. We're interested in the strengths you bring and what you're excited to learn.
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 Remote, Massachusetts is: $115,000-$158,200.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
Build AI that people can hear and experience.
At Bose, we believe sound is the most powerful force on earth. As a Machine Learning / AI Engineer, you'll help bring that belief to life - developing intelligent capabilities for the next generation of audio experiences.
If you enjoy experimenting with models, solving practical problems, and turning ideas into working technology, this is an opportunity to grow your skills while contributing to products and technology that people use every day.
About the Role
You'll help design, train, test, and optimize machine learning models, with a focus on making AI work efficiently on devices with limited memory and computing power. This work brings together Efficient AI and Edge ML: building models that deliver strong results within the constraints of real products.
You'll collaborate with engineers across machine learning, software, embedded systems, and hardware. Along the way, you'll deepen your technical expertise, contribute your ideas, and learn how models move from experimentation toward deployment.
What You'll Do
- Build and experiment. Develop, train, and evaluate machine learning models for consumer audio applications.
- Make models more efficient. Explore ways to improve accuracy while reducing latency, memory use, and computational demands.
- Connect models to products. Partner with software, embedded, and hardware engineers to help bring AI capabilities onto devices.
- Investigate and improve. Analyze results, debug issues, and use testing to guide your next experiment.
- Learn and contribute. Explore emerging ML techniques, share what you discover, and bring fresh ideas to the team.
What You'll Bring
- A bachelor's or advanced degree in Computer Science, Electrical Engineering, Machine Learning, or a related technical field.
- 3+ years of relevant machine learning or AI experience, which may include applicable research or substantial project work.
- A solid foundation in machine learning and deep learning, with hands-on experience building and evaluating models.
- Proficiency in Python and experience with a framework such as PyTorch or TensorFlow.
- Experience training, evaluating, and debugging models-and curiosity about how to make them better.
- An analytical approach to problem-solving, a willingness to ask questions, and enthusiasm for working with others.
Experience That Can Help You Stand Out
You don't need experience in every area below. We're interested in the strengths you bring and what you're excited to learn.
- Techniques such as quantization, pruning, or model compression.
- Edge ML, embedded AI, or deploying models on devices with limited computing resources.
- C/C++ or deployment tools such as ONNX or TensorFlow Lite.
- Audio ML, speech processing, acoustic sensing, or related applications.
- Emerging AI technologies and AI-assisted engineering tools.
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 Remote, Massachusetts is: $115,000-$158,200.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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What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
