Description

Lead the development, optimization, and commercialization of the AI Runtime (QAIRT) SDK on SoCs, focusing on large-scale GenAI model inference.

Responsibilities

• Design, develop, and maintain large-scale C/C++ software stacks using industry best practices.
• Optimize AI workloads across CPU, GPU, and other accelerators to achieve near-GPU performance with minimal power consumption.
• Enable on-device inference of Large Language Models (LLMs) and Large Vision Models (LVMs) leveraging heterogeneous computing architectures.
• Analyze performance bottlenecks and implement low-level optimizations using CUDA and embedded techniques.
• Work closely with hardware, platform, and framework teams to integrate AI capabilities on Snapdragon platforms.

Required Skills

• 10+ years of experience in systems engineering, embedded software, or AI software development.
• Extensive experience in C/C++ development for high-performance or embedded systems.
• Proven experience working with machine learning frameworks such as TensorFlow.
• Hands-on exposure to CUDA programming and performance optimization on heterogeneous platforms.
• Experience deploying and optimizing ML/GenAI models for edge or on-device inference.
• Strong understanding of AI model architectures, especially LLMs and transformer-based models.
• Experience working close to hardware (SoC, CPU/GPU/accelerators).
• Ability to drive complex technical initiatives from concept to production.

Key Skills

Education

Any Graduate