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Tier-1 employer, metro location, and mid-level (3–5 yrs) amplify competition despite niche hardware specialization.
Specialized on-device ML and hardware-accelerated inference skills are industry-specific, limiting cross-industry portability.
Explicit 3–5 year requirement plus mandatory low-level ML, hardware accelerator, and C/C++ expertise increases selectivity.
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Lead development and commercialization of Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs ensuring efficient AI inferencing for large models.
Optimize large C/C++ software stacks for maximum performance on Snapdragon platforms using power-efficient hardware/software integration.
Stay updated with cutting-edge Generative AI models (LLM, LVM) and deploy them effectively at the edge leveraging Qualcomm chipsets.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
3-5 years of relevant software development experience focusing on AI inferencing and embedded/cloud edge software.
Proficiency in C/C++ programming, OS concepts, and scripting skills in Python.
Strong understanding of Generative AI models, quantization, and optimization for AI hardware accelerators (CPU/GPU/NPU).
Experienced in deploying and optimizing large AI models (LLMs, LVMs) on edge devices using Qualcomm hardware.
Skilled in designing and maintaining complex C/C++ software stacks with best practices, including knowledge of design patterns.
Familiar with SIMD architectures, kernel development, Linux/Windows environments, and AI frameworks like PyTorch, TFLite, ONNX Runtime.