Sr. Staff Engineer, AI Models and Applications

Key Responsibilities

• Propose and apply innovative techniques to support both training and inferencing including innovative transformer architectures, parallelism strategies to train on large clusters, low-precision training.
• Implement novel efficient architectures for Generative AI models for training and inference and showcase benefits on AMD.
• Work with open-source framework and community (e.g., PyTorch, JAX, Hugging Face) to integrate AMD optimized models, libraries and publish training recipes.
• Collaborate with software and hardware team to E2E co-optimize performance on current and future AMD solutions.
• Publish and promote your work within AMD and at external venues.

Preferred Experience

• Strong technical expertise in Gen AI model training and inference, and familiarity working with deep learning frameworks like PyTorch/JAX.
• Strong technical expertise in algorithmic innovation towards efficient Gen AI application for both training and inferencing.
• Expertise/publications in one of the areas preferred - efficient model architectures, optimized training, innovative parallelism strategies or low-precision training.
• Experience productizing generative AI models and training foundation model at Scale.
• Excellent written, verbal, and presentation skills, ability to coordinate internally and externally.
• Several years of experience in AI, deep learning and related software development.

Location

San Jose, CA (Hybrid). Can also consider Seattle or Austin locations (Hybrid).