AI Machine Learning Software Engineer, up to Staff (Taipei)

## Company: Qualcomm Semiconductor Limited ## Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software. We are looking for a Senior or Staff level Engineer to work on bleeding-edge AI technology. You will architect high-performance software for AI engines, including Qualcomm AI Engine Direct (QNN), and define the strategy for deploying Large Language Models (LLM) and Vision-Language Models (VLM) on strictly power-constrained hardware. You will collaborate with cross-functional teams (HW/SW architecture) to enhance the world of mobile, edge, and IoT products. This is a great opportunity to innovate and develop leading-edge products around best-in-class Qualcomm AIoT devices. Responsibilities * Architectural Leadership: Lead the development of AI SW stack framework enhancements for optimal resource usage while running complex Transformer-based networks (LLM, ViT) on Qualcomm hardware. * Research to Production: Lead efforts in transitioning research (e.g., new quantization techniques, efficient CLIP encoders) into production-ready solutions, enabling real-world applications and commercial impact.’ * GenAI Optimization: Drive the development of optimization algorithms for ML operators/layers specific to Generative AI (e.g., KV-cache optimization, attention acceleration) within the Qualcomm AI SW stack. * Performance Tuning: Evaluate and optimize neural networks’ runtime performance (latency, memory, power) and accuracy using tools like AIMET and QNN SDK. * Software Development: Develop software tools for profiling and debugging to support the rapid deployment of new neural networks. * Feature Enablement: Work with customer teams to enable state-of-the-art network models and new AI SW features to meet customer use-cases, and collaborate with AI hardware teams to continuously improve our AI solution. Minimum Qualifications * Master's degree in Electrical Engineering, Computer Science, Mathematics, Physics, or a closely related field with 5+ years of relevant experience, or a PhD with 2+ years of experience. * Proficient in modern C, C++, and Python. * Deep experience in neural network deployment, quantization, and model compression (specifically for Transformers/LLMs). * Solid understanding of neural network inference frameworks for embedded systems (e.g., QNN, TFLite, NCNN, ONNX). Preferred Qualifications * 8+ years of experience in embedded Linux development or AI/ML application engineering. * Experience in video/image processing, computer vision, or multimedia algorithm development (relevant for CLIP/Vision tasks). * Hands-on experience with LLM/VLM model pipelines, including fine-tuning, evaluation, and optimization on NPU/DSP. * Experience with Qualcomm AI Stack specifically "AI Engine Direct SDK (QNN)" and "AI Model Efficiency Toolkit (AIMET)". * Familiarity with hardware accelerators (Hexagon DSP) and embedded architectures. Minimum Qualifications: * Master's degree in Engineering, Information Systems, Computer Science, or related field and 5+ years of Software Engineering or related work experience. * OR * PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. * 2+ years of work experience with Programming Language such as...