AI Software Engineer - NPU/Hexagon DSP Kernel Optimization

Job description

Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary We are looking for an embedded software engineer to develop and optimize AI software for Qualcomm NPU and Hexagon DSP processors. The role focuses on high-performance neural network kernels, runtime efficiency, new operator enablement, and close collaboration with architecture teams on next-generation AI platforms. Key Responsibilities - Develop and optimize AI software components for Qualcomm NPU and Hexagon DSP processors. - Implement high-performance neural network kernels/operators with focus on latency, power, memory, and throughput. - Profile runtime bottlenecks and apply hardware-aware software optimizations. - Partner with architecture and hardware teams to improve future NPU and DSP capabilities. - Support customer issue resolution, performance tuning, and platform bring-up. Required Skills and Experience - 2 to 10 years of experience in embedded software development, preferably in AI, DSP, NPU, or performance-critical systems - Strong C/C++ programming skills and solid understanding of processor architecture, operating systems, and multi-processor concepts. - Understanding of deep learning architectures, neural network operators, runtime systems, graph execution, and operator implementation. - Experience with kernel optimization, fixed-point computation, quantization, mathematical/numerical optimization. - Knowledge of memory hierarchy, cache behavior, MMU/IOMMU, bandwidth optimization, and software-hardware co-optimization for AI accelerators. - Exposure to SIMD, vector processing, assembly, profiling, benchmarking, debugging, or low-level optimization techniques. Minimum Qualifications - Bachelors degree in Computer Science, Electrical/Electronic Engineering, or a related field with 2+ years of relevant work experience; or - Masters degree in Computer Science, Electrical/Electronic Engineering, or a related field with 1+ year of relevant work experience. Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience. Or Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience. Or PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.