Principal Engineer, Efficient GenAI
Hybrid (San Jose, CA)$240k - $360kFull-timePosted 3w ago
About the role
Specialized Principal Engineer role within AMD's AI Models and Applications team, focused on enabling efficient Generative AI training and inference at scale on AMD devices, contributing to innovative architectures, distributed training/inference, and collaboration with open-source communities.
Responsibilities
- Propose and apply innovative techniques to support both training and inference, including innovative transformer architectures, parallelism strategies for training on large clusters, inference optimization techniques such as speculative decoding, and optimal KV-caching strategies.
- Implement novel, efficient architectures for Generative AI models for training and inference and showcase the benefits on AMD platforms.
- Work with open-source frameworks and communities (e.g., PyTorch, JAX, vLLM, SGLang) to integrate AMD-optimized models and libraries and publish training recipes.
- Collaborate with software and hardware teams to co-optimize end-to-end performance on current and future AMD solutions.
- Increase adoption of agentic workflows for optimizing and deploying Generative AI applications at scale on AMD platforms.
- Publish and promote your work at external venues, including major conferences.
- Collaborate with researchers within AMD and across industry and academia to promote innovation on AMD platforms.
Qualifications
- PhD or master’s degree in computer science, Electrical Engineering, Mathematics, or a related field.
Skills
Required:Generative AI model training and inferenceAlgorithmic innovation for efficient GenAI applications
Last updated Oct 8, 2026. Interested? Apply on the company site.
About AMD
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AMD delivers leadership high-performance and adaptive computing solutions to advance data center AI, AI PCs, intelligent edge devices, gaming, & beyond.
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