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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Audio/DSP Systems Engineer - **Company:** Analog Devices - **Location:** Wilmington, MA, United States - **Experience:** Expert - **Salary:** $200,000.0 - $275,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Algorithm Design, Systems Engineering, Artificial Neural Networks, Audio Signal Processing, Beamforming, Program Optimization, Profiling, Firmware, Data Flow Control, Python (Programming Language), MATLAB, Tensorflow, Signal Processing, Software Deployment, Systems Architecture, Alwayson, Application Specific Integrated Circuits, Pytorch, Delivery Pipeline, Deep Learning, ONNX (Open Neural Network Exchange) Format - **Published:** June 7, 2026 - **Apply:** https://www.careerjet.com/jobad/use73af1aa59225ad1c23b24fe6c99c871 ## About the Role * PhD in Electrical Engineering, signal processing, or related field * 10+ years in audio/speech signal processing within a semiconductor environment, with significant hands-on deployment experience on DSP and/or NPU platforms * Demonstrated expertise in fixed-point algorithm implementation, model quantization (PTQ/QAT), and cycle-level optimization for resource-constrained processors * Strong working knowledge of simulation-to-RTL flows: bit-exact modeling, RTL co-simulation, and functional verification collaboration with design teams * Proficiency in C (embedded/firmware level), Python, MATLAB, and deep learning frameworks (TensorFlow/TFLite, PyTorch/ONNX) * Experience with low-level profiling tools, instruction set architectures, and memory optimization for embedded AI inference * Solid foundation in array signal processing, beamforming, and acoustic system design, * Direct experience with NPU/accelerator architectures (dataflow engines, weight-stationary/output-stationary designs) and their programming models * Familiarity with ASIC development cycles - from algorithm freeze through tapeout and silicon validation * Background in always-on, sub-mW audio processing for hearable, TWS, or wearable products * Track record of US patents in audio signal processing or embedded ML * Experience technically leading a small engineering team ## Description * 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, maximizing utilization of MAC arrays, SIMD paths, and on-chip memory hierarchies * Profile and optimize inference performance (cycles, memory footprint, power) under strict always-on and real-time constraints typical of hearable/wearable devices * Design and maintain model compression and quantization workflows (PTQ, QAT) with rigorous quality tracking against floating-point baselines * Develop signal processing algorithms for array processing, beamforming, and spatial filtering, with a clear path from MATLAB/Python prototypes to deployable fixed-point implementations * Contribute to audio ASIC system architecture definition - informing hardware spec decisions (precision, buffer sizes, DMA structures, NPU config) based on algorithmic and deployment requirements * Generate IP (patents) and represent the team's technical depth to OEM customers in automotive and hearable segments * Mentor engineers in deployment best practices, embedded optimization, and hardware-aware algorithm design ## Related Videos - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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