Software Dev Engineer II, Stores Foundational AI -SFAI

Key job responsibilities

• Design and implementation of a stable and efficient training system for model training and reinforcement learning that scale to various of model sizes and architecture.
• Collaborate with other talented applied scientists and engineers to improve training efficiency and reliability that accelerates innovation.
• Design and implement scalable data infrastructure: that handle Amazon-scale data ingestion, processing, and delivery across different training and evaluation stages;
• Quickly learn and adopt state-of-the-art technologies and algorithms in the field of Generative AI.

About The Team

The SFAI Training Infrastructure team builds a unified platform for large-scale LLM training, supporting the full lifecycle from pretraining to fine-tuning and RL post-training. We focus on solving hard system challenges at the intersection of distributed systems and machine learning, building a platform that is:

• Scalable — Efficiently train modern model architectures across large-scale compute environments
• Reliable — Enable long-running jobs through fault tolerance, monitoring, and automated recovery
• Efficient — Maximize hardware utilization and throughput through system-level optimizations
• Simple and Unified — Provide a consistent, config-driven interface across models and workflows