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Strong employer brand increases applicants but highly specialized embedded NPU/DSP skillset narrows the pool.
Role requires niche embedded NPU, DSP, and low-power AI expertise, limiting cross-industry transferability.
Explicit degree/experience minima plus specialized DSP/NPU and hardware-software co-design requirements create strict filters.
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Architect and optimize low-power AI (LPAI) DSP and embedded NPU performance on Snapdragon value-tier platforms focusing on scheduling, memory hierarchy, and compression/quantization.
Build system models and conduct performance/power trade studies to drive architectural recommendations scaling across mobile, XR, compute, IoT, and automotive tiers.
Collaborate with hardware/software teams for enhancement deployment, system-level integration, performance testing, and commercialization of DSP/eNPU solutions.
Master’s or PhD in Engineering, Electronics and Communication, Electrical, Computer Science, or related field.
Strong expertise in DSP architecture, embedded NPU design, low-power AI, and performance analysis/benchmarking of embedded processors.
Proficient in Embedded C/C++ programming and familiarity with Python and performance modeling tools.
Work Experience Required: Minimum 1 year of Systems Engineering or related experience with a Master’s degree; 2+ years with Bachelor’s degree; PhD holders also considered.
Experienced in architectural analysis, optimization, and deployment of embedded DSP/NPU solutions targeting low-power AI workloads.
Ability to lead system-level modeling and power/performance tradeoff studies with cross-functional collaboration including hardware and software teams.
Demonstrates hands-on skills in embedded platforms, real-time OS, hardware/software co-design, and AI/ML workload implementations on fixed-point and floating-point architectures.