Edge AI Engineer: Real-Time Audio ML on Embedded Hardware

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

Benefits offered by this job

Bonus programs

Health & welfare benefits

401(k) plan

Employee discount

Job summary

Bose Corporation in Framingham, Massachusetts is seeking an Edge AI ML Engineer to develop, optimize, and deploy ML models for audio and multimodal intelligence on real devices. You will work at the boundary of ML modeling, DSP, and embedded systems, turning research concepts into efficient, robust, production‑ready algorithms.

You will collaborate closely with ML researchers, firmware engineers, and hardware teams to design algorithms that perform well under latency, memory, and power

Qualifications

• Strong proficiency in C/C++ for embedded systems.
• Experience developing and evaluating machine learning models, preferably for audio, speech, or other time-series sensor data.
• Experience optimizing ML models for edge, embedded, or resource-constrained environments.
• Proficiency in Python for model development, experimentation, evaluation, and tooling.

Responsibilities

• Develop and deploy ML models for on-device audio and multimodal intelligence.
• Optimize runtime performance: memory footprint, SRAM usage, latency, and power consumption.
• Integrate ML inference into real-time firmware pipelines.
• Collaborate with ML researchers, firmware engineers, and hardware teams to design efficient algorithms.

Skills

C/C++ for embedded systems

ML model development

Python for ML tooling

Edge/embedded ML optimization

Education

Master’s or Ph.D. in CS/EE/ML or related

Tools

MLIR

Glow

ExecuTorch

TinyML/on-device runtimes

Job description

Bose Corporation in Framingham, Massachusetts is seeking an Edge AI ML Engineer to develop, optimize, and deploy ML models for audio and multimodal intelligence on real devices. You will work at the boundary of ML modeling, DSP, and embedded systems, turning research concepts into efficient, robust, production‑ready algorithms.

You will collaborate closely with ML researchers, firmware engineers, and hardware teams to design algorithms that perform well under latency, memory, and power