Staff Embedded ML/DSP Systems Engineer

13 ago - Milano
analog devices

About Analog Devices
Analog Devices, Inc. (NASDAQ: ADI ) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today’s innovators stay Ahead of What’s Possible™. Learn more at and on LinkedIn and Twitter (X).
Staff Embedded ML/DSP Systems Engineer (Audio Engineering)
About The Role
Join us at Analog Devices as a Staff AI/ML Embedded ML/DSP Systems Engineer and lead the development of cutting-edge AI/ML systems that power real-time applications across industries like industrial automation, data centers, communications, and hardware design. At Analog Devices, we’re committed to pushing the boundaries of innovation in Physical AI. Be at its forefront,



working at the intersection of hardware and software to deliver scalable, production-grade solutions. This role offers the opportunity to drive technical strategy, mentor teams, and shape the future of AI/ML systems.
Key Responsibilities
Responsibilities:
- Architect and optimize end-to-end deployment pipelines for compact audio AI models from trained model through quantization, profiling, and production deployment on DSP/NPU targets
- Define and drive DSP/NPU partitioning strategies, balancing workload allocation, memory bandwidth, latency, and power across processing elements on the SoC
- Own simulation-to-RTL validation flows: develop bit-exact reference models, collaborate with RTL teams on functional verification, and close gaps between algorithmic intent and hardware behavior
- Perform low-level implementation and optimization of signal processing and neural network kernels for fixed-point DSP and NPU instruction sets, maximizi

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