1 day ago
Shanghai, China or Chengdu, ChinaMid Level
Responsibilities
- Develop features and fix bugs in Qualcomm Neural Network SDK and AI Engine Direct SDK.
- Develop neural network operator kernels using Hexagon DSP or SIMD accelerators.
- Optimize model performance and tune accuracy using Qualcomm AI Toolchains.
- Prototype and implement standard and user-defined neural network operators.
- Apply quantization-aware training and post-training quantization.
- Collaborate with regional engineering teams on feature design and implementation.
- Support testing teams in improving AI Toolchain quality.
- Assist customers with deploying neural networks efficiently.
Requirements
- Bachelor’s degree in Engineering, Information Systems, Computer Science, or a related field plus 2+ years of software engineering or related experience; or a master’s degree plus 1+ year; or a PhD in a related field.
- At least 2 years of academic or work experience with programming languages such as C, C++, Java, or Python.
- The posting also lists 3–4 years of software development experience and the ability to independently complete projects on edge platforms.
- Familiarity with ARM architecture-based hardware and software and SDK development for varied system platforms.
- Preferred qualifications include deep learning network implementation, quantization frameworks, model accuracy analysis, debugging, inference frameworks, parallel programming, DSP development, and deployment of ADAS, GenAI, ASR, or NLP models.
- Strong problem-solving, logical thinking, communication, and cross-functional collaboration skills are required.
About Qualcomm
Qualcomm is a public semiconductor company headquartered in San Diego, founded in 1985, that designs and sells wireless chipsets and platforms for mobile devices, automotive, IoT, and networking, notably the Snapdragon application processors and 5G modems. It also licenses a large portfolio of cellular patents to device makers, generating revenue alongside chip sales; its technology underpins many Android smartphones and emerging automotive and edge-compute systems, and it trades on NASDAQ as QCOM.