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Intern - Machine Learning Engineering at Micron Technology

Richardson, Texas, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Feb, 26

Salary

0.0

Posted On

15 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Artificial Intelligence, AI Workflows, Neural Networks, AI Denoising Techniques, Statistics, Data Science, Python, Jupyter, CUDA, OpenCL, C++, Linux, Parallel Computing, Memory Scaling, Benchmarking

Industry

Semiconductor Manufacturing

Description

Researching technologies and tools related to ML and AI Developing and analyzing AI workflows to support use case studies Collaborating with system architects and software engineers to define and influence memory innovations for future compute systems Modifying applications and libraries for technology demonstrations Sharing knowledge with others through white papers and presentations Current PhD or Master's student with the relevant experience below, and must not graduate before September 2026. Experience implementing AI workflows using AI/ML frameworks (PyTorch, TensorFlow, etc.) Deep technical understanding of ML and AI algorithms, neural networks and models. Experience and understanding of AI denoising techniques such as CNNs, GANs and VAEs Knowledge of how compute system architecture and memory scaling impact AI and ML workflows and models Understanding and experience in neural network quantization and LoRA fine-tuning techniques Background in statistics and data science with experience in appropriate tools (e.g. Python, Jupyter) Understanding process variation, disturbances, wear-out and other error sources in semiconductor memories, and how it influences error detection & correction requirements Experience with application performance benchmarking on heterogeneous (CPU + GPU) systems Experience programming GPUs (CUDA, OpenCL, SYCL, etc.) Python and C++ programming experience in a Linux environment Familiarity with compute scaling, parallel computing and shared memory technologies (CXL, NvLink, UALink, OpenMP, MPI, etc.) is desired Willingness to work on a varying mix of research- and demonstration-focused assignments depending on the changing needs of a pathfinding organization

Responsibilities

The intern will research technologies and tools related to machine learning and AI, develop and analyze AI workflows, and collaborate with system architects and software engineers. They will also modify applications for technology demonstrations and share knowledge through white papers and presentations.