name : Moksha Choksi
college : IIIT Hyderabad (ECE, class of 2028)
focus : ML systems · Distributed systems · Full-stack engineering
intern : Technology Intern @ Chubb — shipped production LRU cache in Java/Spring Boot
jee : 99.78 percentile (AIR 3609)
looking_for : SWE / ML / backend internships — Winter 2026 / Summer 2027I like problems where correctness and performance both matter whether that's a caching layer taking load off a production DB, a distributed file system failing over without dropping data, or an ML pipeline that actually generalises. Less "hello world", more "what happens at 1000 concurrent clients".
Technology Intern - Chubb Jun 2025 – Jul 2025
Architected and deployed a production-grade caching layer to eliminate redundant DB queries in live backend services. Built an LRU cache from scratch in Java with TTL expiry, full REST management API, CLI tooling for ops, and a background cleanup thread. System went to production.
Java Spring Boot LRU Cache TTL REST API Distributed Systems
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🌐 Distributed Network File System TCP-based NFS from scratch in C. Distributed client-server model with file striping across 1000+ nodes, support for 1000+ concurrent clients, automatic failover, and real-time data replication.
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🗺️ Geolocate — Image Geolocation End-to-end ML pipeline: image → (lat, lng, region). Deep learning ensemble in PyTorch + k-NN post-processing. Handles data preprocessing, training, and inference from a single pipeline.
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Full-stack MERN chatbot with OpenAI integration, context-aware conversations, and a security-conscious auth layer using HTTP-only cookies for session management.
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💾 LRU Cache System (@ Chubb) Production caching system in Java. Memory-efficient LRU with TTL expiry, REST APIs for dynamic management, CLI for admin ops, background cleanup. Reduced latency on live services.
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Languages
ML / Data
Backend & Systems
Frontend & DB
Core areas · DSA Operating Systems Computer Networks Distributed Systems Caching OOP
