Rahul Ganesan I build AI systems and full-stack products end-to-end from GPU inference infrastructure to React/TypeScript frontends to published developer tooling without needing a playbook. In the past 12 months, some of the projects I've shipped: - a vLLM inference server with Redis backpressure and Prometheus observability (5ms cache hit)- an LLM evaluation harness over HumanEval+ that exposed flaws in how benchmark scores are typically computed- a LangGraph multi-agent tool that routes between Notion and web search via MCP (22% reliability gain)- a React/TypeScript analytics SaaS with JWT RBAC and optimized MySQL aggregations (40% query latency reduction); and - an open-source Cursor agent skill that does UX audits (link featured below in next section)I'm most useful when the problem isn't fully defined, and when the stack isn't decided, and the team needs someone who can scope the system, own it from design to deployment, and know whether it worked.Looking for a early-stage engineering role where the problems are hard and the team is small.
Data Engineer Intern
Technical Lead - Natural Language Processing
Machine Learning Research Intern
Data Science and Business Analytics Intern
Masters, Science
Bachelors, Software
Vocational, Science
Secondary, Software
