Ai Software Engineer - Npu/Hexagon Dsp Kernel Optimization

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

• Bachelor's 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.
• Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
• PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.