Company:
Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering
General Summary:
About us:
We are Qualcomm AI Research that are advancing AI to make its core capabilities – perception, reasoning, and action – ubiquitous across devices. Our mission is to make breakthroughs in fundamental AI research and scale them across industries. By bringing together some of the best minds in the field, we're pushing the boundaries of what's possible and shaping the future of AI. Welcome to visit our website at AI Research Areas | Intelligence on Devices | Qualcomm
Key Responsibilities:
- Design and develop end-to-end AI tools, models, and software to enable efficient deployment of quantized neural networks on cutting-edge Qualcomm hardware, with a strong focus on optimizing performance for speed, latency, memory, and power consumption
- Deploy AI models to Qualcomm CPU/NPU/GPU using the QNN SDK toolchain
- Implement and optimize inference drivers for large language models (LLM) and large multimodal models (LMM)
- Develop debugging and profiling tools, as well as Qualcomm SDK solutions, to solve software issues and facilitate rapid on-device deployment of quantized models
- Build and maintain automated test suites leveraging modern testing tools and frameworks
- Collaborate closely with cross-functional teams to gather requirements and design development/test approaches
- Analyze test results and provide actionable feedback to the core development team
Preferred Skills and Experience:
- Proficiency in Python and C/C++
- Strong skills in software design, development, and debugging
- Hands-on experience with generative AI models, including LLMs and LVMs
- Solid understanding of deep learning and experience with popular frameworks such as PyTorch, transformer and the Hugging Face ecosystem
- Knowledge of LLM/LMM inference engines, such as llama.cpp or ExecuTorch
- Experience working with the Qualcomm QNN SDK is highly desirable
- Experience working with the Qualcomm inference driver Genie is highly desirable
- Knowledge of neural network quantization techniques is a significant advantage
- Experience with Android programming is a plus
- Experience using AI coding assistants such as Claude code, Codex, or Cursor is a plus
Minimum Qualifications:
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer Science, Engineering, Information Systems, or related field and 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
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