ML/AI Intern Co-op — Research & Impact

AMD

Santa Clara (CA)

Hybrid

USD 28,000 - 55,000

Full time

14 days+

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Benefits offered by this job

AMD benefits at a glance
Equal opportunity employer

Job summary

AMD is seeking a highly motivated Machine Learning/AI intern/co-op to join our team at the forefront of AI research and development. You will work with experienced ML engineers on next-generation product differentiation features and gain real-world experience across AI-focused projects.

You will learn new technologies, analyze and implement changes to algorithms to improve AI performance and user experiences, and contribute to work that impacts millions of end-users worldwide.

Qualifications

  • Currently enrolled in a US-based university pursuing an undergraduate degree in a related field (CS/CE/Data Science).
  • Knowledge of ML, data science, computer vision, statistics, and math; experience with Python and C/C++.
  • Familiar with ML frameworks (PyTorch, TensorFlow) and cloud platforms (AWS/GCP/Azure).

Responsibilities

  • Assist in research and development of ML/AI features for AMD products.
  • Analyze and implement changes to algorithms to improve AI performance and user experiences.
  • Collaborate with ML engineers on projects involving source code analysis and image processing.

Skills

Machine learning
Data science
Computer vision
Statistics
Programming Python
C/C++
SQL & NoSQL
ML frameworks
PyTorch
TensorFlow

Education

Undergraduate degree in CS/CE/Data Science

Tools

Python
C/C++
PyTorch
TensorFlow
Cloud platforms (AWS/GCP/Azure)
SQL/NoSQL databases

Job description

AMD is seeking a highly motivated Machine Learning/AI intern/co-op to join our team at the forefront of AI research and development. You will work with experienced ML engineers on next-generation product differentiation features and gain real-world experience across AI-focused projects.

You will learn new technologies, analyze and implement changes to algorithms to improve AI performance and user experiences, and contribute to work that impacts millions of end-users worldwide.

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