Senior AI/ML Architect - Edge & Embedded Systems

Via Licensing Corporation

Atlanta (GA)

On-site

USD 176,000 - 215,000

Full time

14 days+

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Benefits offered by this job

Flex Work
Competitive compensation
Excellent benefits

Job summary

Dolby is seeking a Senior Staff AI/ML Architect to bridge research and product engineering, translating advanced ML research into scalable, production-ready solutions across Dolby’s portfolio.

You will lead technical strategy for training and deploying AI/ML models on edge and embedded platforms, collaborating with researchers, software engineers, and silicon partners to shape the roadmap and ensure robust, efficient implementations.

Qualifications

  • Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or related field.

Responsibilities

  • Define and guide AI/ML technology strategy across Dolby’s core tech areas (audio/video processing, personalization) with edge/embedded focus.
  • Serve as primary interface between ML research and engineering teams.
  • Define architectural approaches to integrate DSPs/hardware accelerators with ML models.
  • Collaborate with Data Eng to establish data governance and pipelines.
  • Work with QA to develop testing methodologies for AI/ML systems.

Skills

Hands-on AI/ML engineering
Embedded software engineering
Production code & pipelines
PyTorch/TensorFlow/JAX/ONNX
Edge/on-device ML
DSP/ hardware accelerators
Audio/Video processing

Education

Bachelor’s or Master’s in Electrical Eng/CS or related field

Tools

PyTorch
TensorFlow
ONNX
QNN/Hexagon toolchains
Profiling/benchmarking tools

Job description

Dolby is seeking a Senior Staff AI/ML Architect to bridge research and product engineering, translating advanced ML research into scalable, production-ready solutions across Dolby’s portfolio.

You will lead technical strategy for training and deploying AI/ML models on edge and embedded platforms, collaborating with researchers, software engineers, and silicon partners to shape the roadmap and ensure robust, efficient implementations.

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