Principal Audio/DSP Systems Engineer

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
• 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
• Develop model compression and quantization workflows (PTQ, QAT) with rigorous quality tracking against floating-point baselines
• Design and maintain model compression and quantization workflows (PTQ, QAT) with rigorous quality tracking against floating-point baselines
• 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

Requirements

• 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

Preferred Qualifications

• 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