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Machine Learning, AI Engineer
Bose Corporation. Develop, train, and evaluate machine learning models for consumer audio applications .
Posted 11/3/2026full-timeRemote • Massachusetts • United StatesMid-LevelSenior💰 $115,000 - $158,200 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and evaluating machine learning models for consumer audio applications, with a strong foundation in deep learning and proficiency in Python. Capable of collaborating with cross-functional teams to deploy AI solutions on devices with limited computing resources.
Highest-signal resume keywords
Machine LearningDeep LearningPython ProficiencyModel EvaluationEmbedded AI
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningDeep LearningModel EvaluationQuantizationPruningModel CompressionAudio MLSpeech ProcessingC/C++Debugging
Tools & Technologies
PyTorchTensorFlowONNXTensorFlow Lite
Industry Keywords
Consumer Audio ApplicationsEdge MLEmbedded AIAI TechnologiesAI-Assisted Engineering Tools
Tech Stack
Tools & technologiesPythonPyTorchTensorflowC++
About the role
Key responsibilities & impact- Develop, train, and evaluate machine learning models for consumer audio applications
- Improve model accuracy while reducing latency, memory use, and computational demands
- Partner with software, embedded, and hardware engineers to bring AI capabilities onto devices
- Analyze results, debug issues, and use testing to guide experiments
- Explore emerging ML techniques, share discoveries, and contribute ideas to the team
Requirements
What you’ll need- 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, including applicable research or substantial project work
- Solid foundation in machine learning and deep learning
- Hands-on experience building and evaluating models
- Proficiency in Python
- Experience with PyTorch or TensorFlow
- Experience training, evaluating, and debugging models
- 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
Benefits
Comp & perks- Bonus programs
- Comprehensive health and welfare benefits
- 401(k) plan
- Exclusive perks designed to support wellbeing
- Generous employee discount
- Competitive base pay