Machine Learning/AI Software Intern

Machine Learning/AI Software Intern at Qualcomm

As a Machine Learning/AI Software Intern at Qualcomm, you will join our AI team to contribute to the software design and implementation of model deployment in edge devices. This role offers an exceptional opportunity to gain practical experience in a fast-evolving field, focusing on projects involving model compression, quantization, conversion, and on-device deployment, making a significant impact on cutting-edge technology.

Key Responsibilities

• Develop end-to-end AI tools, models, or software for running quantized neural network models on Qualcomm's leading-edge hardware with optimal resource utilization.
• Design and develop comprehensive end-to-end test strategies and frameworks for complex software systems.
• Create and maintain automated test suites utilizing modern testing tools and frameworks.
• Develop debugging and profiling tools, along with Qualcomm SDK, for rapid deployment of quantized models on devices.
• Actively participate in code reviews and contribute to enhancing test coverage and code quality.
• Collaborate effectively with cross-functional teams to understand requirements and devise appropriate test approaches.
• Analyze test results thoroughly and provide detailed, actionable feedback to the development team.
• Conduct experiments to reproduce and optimize the accuracy and performance of various AI models.
• Engage in related paper reading, summarization, and presentation of findings.

Qualifications

• Currently pursuing or recently completed a degree in Computer Science, Artificial Intelligence, Electrical Engineering, or a closely related technical field.
• Demonstrated experience with large language models (LLM), vision-language models (VLM), and large vision models (LVM), including familiarity with diffusers, multi-modality, CNNs, RNN/LSTMs, Transformers, and other relevant architectures.
• Practical experience in model quantization, compression, and deployment specifically on smartphones or other edge devices.
• Strong foundational mathematical skills, including linear algebra, matrix operations, differential algebra, and statistics.

Preferred Skills

• Proficiency in C++ and Python programming languages.
• Experience with machine learning and deep learning algorithms and architectures, such as CNNs, RNN/LSTMs, Transformers, LVM, and LLM.
• Hands-on experience with popular ML frameworks, including TensorFlow, PyTorch, and Onnx Runtime.
• Knowledge of on-device AI model deployment is a significant advantage.
• Familiarity with llama.cpp or ExecuTorch is a plus.
• Understanding of Qualcomm SNPE/QNN SDK is also beneficial.

Key skills/competency

• Machine Learning
• Artificial Intelligence
• Deep Learning
• Model Quantization
• Edge Device Deployment
• Python
• C++
• TensorFlow
• PyTorch
• Neural Networks
• LLM