Back
Tier-1 employer, metro location and mid-level ML role increase competition despite niche on-device accelerator specialization.
Requires specialized on-device ML and hardware-accelerator skills, limiting cross-industry transferability.
Explicit 4+ years requirement plus mandatory ML quantization, kernel and accelerator expertise enforce strict screening.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and optimize software to enable on-device inference of Generative AI models on Qualcomm chipsets leveraging heterogeneous computing capabilities.
Implement and optimize algorithms for AI hardware accelerators including CPU, GPU, and NPU focusing on power-efficient execution of large language and vision models.
Collaborate with a globally diverse team to integrate and validate AI software solutions on Snapdragon platforms at near GPU speeds.
Bachelor's degree in Engineering, Computer Science, Information Systems or related field with 4+ years software engineering experience OR Master's with 3+ years OR PhD with 2+ years.
2+ years programming experience in languages such as C, C++, Java, or Python.
Strong understanding of floating-point, fixed-point representations and quantization concepts for AI hardware.
Experience optimizing algorithms for AI hardware accelerators (CPU/GPU/NPU).
Experience with SIMD processor architecture and system-level software/kernel development targeted at SIMD architectures.
Familiarity with AI frameworks and runtimes like PyTorch, TFLite, ONNX Runtime, llama.cpp, MLX, or MLC is preferred.
Knowledge or experience with parallel computing languages/systems like OpenCL and CUDA and comfortable working in Linux and Windows environments.