FY25 Intern – GenAI Evaluation and Benchmarking Internship

Deep Learning Research Internship (4 months Summer 2025) 

Qualcomm AI Research looking for talented machine learning algorithm evaluation engineers with experience in machine learning to enable embedded deep learning.

Come join a high-caliber team of engineers building advanced machine learning technology, best-in-class solutions, and user friendly model optimization tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet) to enable state-of-the-art networks to run on devices with limited power, memory, and computation.

We solve challenging problems to improve speed, accuracy, and power-consumption of ML models. We optimize state-of-the-art networks to run on mobile platforms in real-time through advanced quantization and compression techniques, and cover a variety of deep learning technology areas, e.g. Convolutional neural networks, deep generative models, Large language vision, and multimodal models.

Programming Languages: 

• Python

• Pytorch

• ONNX

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field

• Great at software development with excellent analytical, development, and debugging skills

• Strong understanding of Machine Learning fundamentals

• Understanding of generative AI and its usage in various application

• Knowledge of machine learning libraries such as TensorFlow, PyTorch is essential

• Excellent interpersonal, written, and oral communications skills

Preferred Qualifications:

• MS or PhD in Computer Science/Engineering with 1+ years of professional experience or equivalent experience

• 2+ years of proven experience in software development for machine learning or high-performance computing with strong programming skills in Python and software design

• Proficiency in designing, implementing and training DL/RL algorithms in high-level languages/frameworks (PyTorch and TensorFlow)

• Strong background in at least one of the following fields: Large Language models; Diffusion models; Model compression / quantization / optimization for embedded devices; Computer vision; Audio and speech / NLP; Deep Generative

• Experience with improving efficiency of AI algorithms for deployment, including familiarity with open source solutions such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit (https://github.com/quic/aimet)

• LLM or Diffusion model training, finetuning.

Educational Requirements:

• In study towards a Masters or PhD in the following: 

Computer Science, Computer Engineering, Electrical Engineering with a graduation date of December-2025 or later

• Looking 1 Summer Co-op (May - August)