Lead Engineer, Senior-Machine Learning Tools

Role Overview: Join the exciting Generative AI team at Qualcomm focused on integrating cutting edge GenAI models on Qualcomm chipsets. You will work with Qualcomm chips extensive heterogeneous computing capabilities to allow inference of GenAI models on-device without the need for connection to the cloud. Your role involves spearheading the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs. As an AI inferencing expert, you will push the limits of performance from large models and deploy large C/C++ software stacks using best practices. Your responsibilities will include staying updated on GenAI advancements, understanding LLMs/Transformers, and the nuances of edge-based GenAI deployment. Your passion for the role of edge in AI's evolution will be a key driving force in this role. Key Responsibilities: - Spearhead the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs - Push the limits of performance from large models - Deploy large C/C++ software stacks using best practices - Stay updated on GenAI advancements, understanding LLMs/Transformers, and the nuances of edge-based GenAI deployment - Utilize power efficient hardware and Software stack to run Large Language Models (LLMs) and Large Vision Models (LVM) at near GPU speeds Qualifications Required: - Masters/Bachelors degree in computer science or equivalent - 6+ years of relevant work experience in software development - Strong understanding of Generative AI models LLM, LVM, LMMs and building blocks (self-attention, cross attention, kv caching etc.) - Knowledge of floating-point, fixed-point representations, and quantization concepts - Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU) - Proficient in C/C++ programming, Design Patterns, and OS concepts - Good scripting skills in Python - Excellent analytical and debugging skills - Good communication skills (verbal, presentation, written) - Ability to collaborate across a globally diverse team and multiple interests Role Overview: Join the exciting Generative AI team at Qualcomm focused on integrating cutting edge GenAI models on Qualcomm chipsets. You will work with Qualcomm chips extensive heterogeneous computing capabilities to allow inference of GenAI models on-device without the need for connection to the cloud. Your role involves spearheading the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs. As an AI inferencing expert, you will push the limits of performance from large models and deploy large C/C++ software stacks using best practices. Your responsibilities will include staying updated on GenAI advancements, understanding LLMs/Transformers, and the nuances of edge-based GenAI deployment. Your passion for the role of edge in AI's evolution will be a key driving force in this role. Key Responsibilities: - Spearhead the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs - Push the limits of performance from large models - Deploy large C/C++ software stacks using best practices - Stay updated on GenAI advancements, understanding LLMs/Transformers, and the nuances of edge-based GenAI deployment - Utilize power efficient hardware and Software stack to run Large Language Models (LLMs) and Large Vision Models (LVM) at near GPU speeds Qualifications Required: - Masters/Bachelors degree in computer science or equivalent - 6+ years of relevant work experience in software development - Strong understanding of Generative AI models LLM, LVM, LMMs and building blocks (self-attention, cross attention, kv caching etc.) - Knowledge of floating-point, fixed-point representations, and quantization concepts - Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU) - Proficient in C/C++ programming, Design Patterns, and OS concepts - Good scripting skills in Python - Excellent analytical and debugging skills - Good communication skills (verbal, presentation, written) - Ability to collaborate across a globally diverse team and multiple interests