Computer Science undergraduate (AI & ML specialization)
Focused on backend systems, applied AI/ML, cloud fundamentals, and open-source development

• Building and implementing AI/ML-driven systems for real-world use cases
• Designing backend components that support data processing, APIs, and ML workflows
• Exploring cloud computing fundamentals (AWS basics, infrastructure concepts)
• Contributing to open-source projects and understanding large, long-lived systems

• Advanced AI/ML system integration, including LLM-based applications and RAG architectures
• Working with large datasets, backend services, and scalable data pipelines
• Understanding how open-source systems handle large databases and long-running services
• Writing cleaner, testable code and improving code review practices

• An AI-focused Retrieval-Augmented Generation (RAG) system for document ingestion, semantic search, and structured reasoning
• Working on system architecture, retrieval workflows, and integration with language models

• Contributing to Wayback Machine–related archiving and data processing projects
• Learning how large-scale archival systems manage massive datasets and long-term storage

• Contributing to the backend and developer workflow codebase
• Working on onboarding issues while learning contribution standards and project architecture

Languages

Backend, AI & Tooling

Databases