Salary: $32,000 - 52,000 per year
Requirements:
• Currently enrolled in a US-based university in a PhD program in computer science, computer engineering, data science/analytics, or a related field
• Familiarity with machine learning, data science, computer vision, statistics, and mathematics
• Proficient in programming languages such as Python and C/C++
• Experience with relational (SQL) and no-SQL databases
• Knowledge of machine learning algorithms and frameworks
• Understanding of deep learning/AI frameworks like PyTorch, TensorFlow, or Caffe
• Basic knowledge of cloud services (e.g., AWS, GCP, Azure)
Responsibilities:
• Participate in research and development of innovative product differentiation features in collaboration with expert ML/AI engineers
• Explore and implement new technologies in Machine Learning, AI, and High-Performance Computing
• Analyze and enhance algorithms to boost AI performance and improve user experiences
• Engage in project work related to machine learning applications for source code analysis and image corruption detection
• Contribute to the research, development, and deployment of machine learning and computer vision products for current and future AMD offerings
• Troubleshoot and resolve issues with deployed AI to enhance user satisfaction
• Assist AI software teams in planning, developing collateral, and engaging with customers
Technologies:
• AI
• AWS
• Azure
• Cloud
• Computer Vision
• Embedded
• GCP
• Machine Learning
• PyTorch
• Python
• SQL
• TensorFlow
• Support
• Network
More:
At AMD, we drive innovation to create advanced products that transform computing experiences in AI, data centers, PCs, gaming, and embedded systems. Our culture promotes collaboration, creativity, and inclusion, allowing our team to tackle significant global challenges. When you join us, youll be part of a dynamic environment that not only fosters your personal growth but also positions you to make a meaningful impact in technology. This internship opportunity is based in various locations, including Austin, TX; Boxborough, MA; Fort Collins, CO; and more, allowing for a full-time schedule in either onsite or hybrid capacities.
last updated 6 week of 2026
