Edge AI ML Engineer

Bose
United States
Workplace: OnsiteFull timeUSD 141,000 - 193,950 annuallyFunction: Data Science & Machine LearningEducation: mastersSkills: ["Ownership","End-to-end thinking","Problem-solving"]

Develop, optimize, and deploy audio and multimodal machine learning models for edge devices, bridging ML modeling with DSP and embedded systems. Build and iterate on real-world sensing and interaction models under constraints like latency, memory, and power. Implement embedded inference pipelines on RTOS environments, convert models into efficient fixed-point implementations, and optimize performance across MCUs, DSPs, and NPUs using on-device runtimes and modular embedded platform components.

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FursaFursa
Bose
Bose
3 days ago

Edge AI ML Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Develop, optimize, and deploy audio and multimodal machine learning models for edge devices, bridging ML modeling with DSP and embedded systems. Build and iterate on real-world sensing and interaction models under constraints like latency, memory, and power. Implement embedded inference pipelines on RTOS environments, convert models into efficient fixed-point implementations, and optimize performance across MCUs, DSPs, and NPUs using on-device runtimes and modular embedded platform components.
Location: United States
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Develop, optimize, and deploy audio and multimodal ML models for edge devices, iterating on models for real-world sensing and interaction use cases.
  • •Build embedded software for RTOS environments and deploy models to device runtimes and hardware accelerators (DSP, NPU, MCU).
  • •Convert trained ML models into efficient embedded implementations using C/C++, quantization, and fixed-point inference, optimizing memory, SRAM, latency, and power.
  • •Integrate ML inference into real-time firmware pipelines and design end-to-end embedded AI systems (sensor to preprocessing to model to post-processing).
  • •Architect reusable embedded ML platform components across hardware targets and profile/optimize performance on MCUs, DSP cores, NPUs, and custom accelerators.

Pay and Benefits

Salary: USD 141,000 - 193,950 annually
Perks:Health Insurance401kEmployee Discount

Key Requirements

  • •Strong proficiency in C/C++ for embedded systems.
  • •Strong experience developing and evaluating machine learning models, preferably for audio, speech, or 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.
  • •Master’s or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, or a related field.
Education:Master's in Computer Science, Electrical Engineering, Machine Learning, or related field
Skills:OwnershipEnd-to-end thinkingProblem-solving
Tech Stack:CC++PythonDSPFreeRTOSCMakeC/C++QuantizationFixed-point inferenceTFLite MicroExecuTorchMCUDSP coreNPUCustom acceleratorsRTOSCross-compilation toolchains

Company Brief

Bose
Designs, manufactures, and sells high-fidelity audio equipment including headphones, speakers, home audio systems, and professional sound solutions. Known for research-driven innovation in acoustics and consumer audio products worldwide.
Industry: Consumer Electronics
Company Size: Enterprise (1,001+ employees)
Growth: Established Company
Headquarters: Framingham, United States
Founded: 1964
WebsiteLinkedIn