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Generative AI Engineer - Graphics

Job in San Jose, Santa Clara County, California, 95173, USA
Listing for: AMD
Full Time position
Listed on 2026-10-19
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture.

We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.  Together, we advance your career.  

THE ROLE AMD is seeking an experienced AI/ML Engineer to join our Applied Research and Engineering team focused on advancing the next generation of Generative AI technologies. In this role, you will develop and optimize state-of-the-art AI models for image generation, diffusion-based learning, and multimodal applications that push the boundaries of visual computing. You will work alongside industry-leading researchers, software engineers, and hardware architects to build innovative AI solutions that leverage AMD’s latest GPU technologies and accelerate the future of content creation, graphics, and intelligent computing.

THE PERSONThe ideal candidate is passionate about Generative AI, machine learning, and developing cutting-edge models that solve complex real-world problems. You are comfortable working in a fast-paced research and engineering environment, possess strong software development skills, and enjoy collaborating across multidisciplinary teams. You have a deep understanding of modern AI architecture and are excited about translating research into production-scale solutions.

KEY RESPONSIBILITIES Develop, train, fine-tune, and optimize Generative AI models for image generation and visual content creation.

Design and implement diffusion models, multimodal architectures, and advanced machine learning algorithms.

Build scalable training and inference pipelines leveraging high-performance GPU computing.

Evaluate model quality, performance, and efficiency using state-of-the-art techniques and benchmarks.

Collaborate with research, software, and hardware teams to integrate AI innovations into AMD technologies.

Optimize AI workloads for AMD GPU architectures and contribute to performance analysis and improvements.

Stay current with emerging advancements in Generative AI, image synthesis, diffusion models, and large-scale machine learning.

PREFERRED EXPERIENCE Strong software development experience in Python and C++.Deep understanding of machine learning, deep learning, and neural network architectures.

Experience developing and training diffusion models, image generation models, GANs, transformers, or multimodal AI systems.

Hands-on experience with PyTorch, Tensor Flow, JAX, or similar machine learning frameworks.

Experience fine-tuning and deploying large-scale AI models.

Familiarity with distributed training, model optimization, and GPU acceleration techniques.

Experience building AI training and inference pipelines in production environments.

Knowledge of computer vision, image synthesis, and multimodal learning techniques.

Experience with MLOps, CI/CD workflows, Git, and modern software engineering practices.

Experience leveraging AI coding assistants, agentic AI systems, or automated development workflows.

Strong communication, collaboration, and problem-solving skills.

ACADEMIC CREDENTIALSMaster's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Engineering, or a related technical field preferred.

LOCATION:

San Jose, California#LI-JE1

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