Edge ML Engineer: Efficient AI for Audio

Bose Corporation, U.S.A; Framingham (MA); On-site; USD 141,000 - 194,000; Full time

Benefits offered by this job

Bonus programs

Health and welfare benefits

401(k) plan

Employee discount

Job summary

Bose Corporation seeks a Machine Learning Engineer to design, train, and optimize models for next-generation audio products. You will work with embedded, DSP, and hardware teams to deploy AI on resource-constrained devices, balancing accuracy, latency, and power.

Strong ML fundamentals and experience with edge deployments are essential. The role emphasizes collaboration, iterative development, and continuous improvement across model development, deployment, and validation workflows, with a focus

Qualifications

• MS/PhD in Computer Science, Electrical Engineering, Computer Engineering, Machine Learning, or related field.
• Strong ML fundamentals including model design, training, evaluation, and optimization.
• Proficiency with Efficient ML techniques: quantization, pruning, knowledge distillation, model compression, and efficient architectures.
• Understanding how optimization affects accuracy, latency, memory footprint, compute requirements, and deployment compatibility.
• Proficiency with deep learning frameworks such as PyTorch, TensorFlow, or similar.
• Strong Python programming, debugging, and problem-solving skills.
• Working knowledge of C/C++ and collaboration with embedded/production teams.
• Understanding of Edge ML concepts and resource constraints (compute, memory, latency, power).

Responsibilities

• Design, train, evaluate, and optimize machine learning models for consumer audio products.
• Apply Efficient ML techniques (quantization, pruning, distillation, model compression) to improve efficiency while preserving quality.
• Collaborate with embedded, DSP, compiler, and hardware engineers to deploy models on resource-constrained platforms.
• Analyze deployment feedback, identify model-related issues, and iterate on architectures and training methods.
• Adapt models to platform constraints like unsupported operators, memory usage, latency, compute requirements and power.
• Profile and evaluate model performance across accuracy, latency, memory footprint, model size, compute efficiency and power usage.
• Develop and maintain repeatable workflows for model training, conversion, compilation, simulation, validation, and performance analysis.
• Collaborate across ML, embedded software, DSP, hardware, compiler, and product engineering teams for production-ready AI solutions.
• Evaluate emerging ML technologies and AI-assisted engineering tools to improve workflows.
• Document experiments, deployment learnings, and reusable engineering practices.
• Mentor interns and co-op engineers.

Job description

Bose Corporation seeks a Machine Learning Engineer to design, train, and optimize models for next-generation audio products. You will work with embedded, DSP, and hardware teams to deploy AI on resource-constrained devices, balancing accuracy, latency, and power.

Strong ML fundamentals and experience with edge deployments are essential. The role emphasizes collaboration, iterative development, and continuous improvement across model development, deployment, and validation workflows, with a focus