Worked on the kvcache-ai/sglang repository to deliver mixed chunk processing support for attention in non-MLA configurations, focusing on backend development and deep learning. The approach involved introducing new Python classes and methods to manage attention masks, which improved both configurability and performance for targeted scenarios. By enhancing the attention mechanism’s flexibility, the work enabled higher-throughput attention paths and reduced latency in non-MLA setups. These architectural changes established a foundation for broader deployment across hardware variants and future optimizations. The work leveraged skills in machine learning and PyTorch, emphasizing maintainable code and targeted performance improvements within the project’s backend systems.