Company:

Qualcomm China

Job Area:

Engineering Group, Engineering Group > Machine Learning Engineering

General Summary:

Responsibility:

• Development of end-to-end AI tools, models or software for agentic AI system on Qualcomm leading edge hardware with optimal resource

• Design and develop end-to-end test strategies and frameworks for complex agentic AI system

• Create and maintain automated test suites using modern testing tools and frameworks

• Development of debugging/profiling tools and Qualcomm SDK to rapid deployment quantized models on device

• Participate in code reviews and contribute to improving test coverage

• Collaborate with cross-functional teams to understand requirements and design test approaches

• Analyze test results and provide detailed feedback to development team

Preferred Skills and Experience:

• 2 years of work experience in relevant fields

• Hands-on experience with generative AI models, including LLMs and LVMs

• Excellent programming capability with software design, development, and debugging in Python (C/C++ is a plus)

• Knowledge in deep learning frameworks like Py Torch or Tensorflow

• Knowledge in transformers and Huggingface library

• Experience with Agentic AI pipeline and workflow

• Experience with Qualcomm QNN SDK is a plus

• Practical experience with Release + CI/CD Pipeline for end-to-end integration, regression, stress, performance

• Familiarity with device database such as Meta FAISS, SQL dB is a plus

• Experience with Android programming and trace analysis 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 2+ 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 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  OR
  PhD in Computer Science, Engineering, Information Systems, or related field.

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