Aaradhya Mehra
@aaradhyamehra
AI/ML-focused software engineer building production RAG and LLM pipelines with verified citations and efficient caching.
What I'm looking for
I’m a computer science undergraduate building practical, production-grade AI systems—especially RAG and LLM applications designed to reduce hallucinations and improve reliability.
In my projects, I focused on measurable outcomes. I built a support knowledge copilot with verified, hallucination-checked citations, using a hybrid retrieval pipeline (dense embeddings + BM25) and LLM-as-judge validation to boost accuracy from 72% to 88%.
I also engineered an “LLM semantic cache gateway” that detects semantically similar requests to cut cost and latency. It reduced simulated API cost by 40% and lowered P95 latency by 65%, with similarity-threshold tuning plus LLM-as-judge checks to prevent incorrect cache hits and enforce safe caching policies.
I enjoy combining strong backend engineering (FastAPI, REST APIs, Docker) with evaluation-driven development—using golden sets and load testing—so the systems I ship are not just demos, but dependable tools.
Experience
Work history, roles, and key accomplishments
B.Tech in Computer Science
Bangalore Institute of Technology
Sep 2023 - Present (2 years 11 months)
Undergraduate in Computer Science Engineering (CGPA 8.5/10), graduating June 2027. Builds and deploys ML/LLM models using Python, scikit-learn, and Hugging Face, with work on production-oriented AI applications using REST APIs and cloud deployment.
Augmentix Hackathon (2nd Place)
NMIT Bangalore
Jan 2026 - Present (7 months)
Secured 2nd place at the Augmentix Hackathon. Built MolGenix in 36 hours with a team, owning a FastAPI backend and an ML-based molecular docking pipeline.
Full Stack GenAI & Agentic AI
Completed a Full Stack Generative & Agentic AI course using Python. Covered RAG pipelines with LangChain and multi-node/stateful agents with LangGraph using vector databases.
Machine Learning A–Z
Completed a Machine Learning A–Z course in Python. Built regression, classification, clustering, and NLP pipelines using scikit-learn.
C++ DSA — Abdul Bari
Completed a C++ DSA certification focused on core data structures and algorithms. Covered graph algorithms, dynamic programming, trees, and time/space complexity analysis in C++.
Competitive Programming
LeetCode & Codeforces
Solved 250+ algorithmic problems across LeetCode and Codeforces, achieving a Pupil rating through rated contests.
SIH Internal Qualifier (Selected)
Smart India Hackathon (SIH)
Qualified for the institute-level selection for the Smart India Hackathon by designing a federated learning solution. Led system architecture and delivered the technical presentation for the submission.
Education
Degrees, certifications, and relevant coursework
Bangalore Institute of Technology
Bachelor of Technology, Computer Science Engineering
2023 - 2027
Grade: CGPA: 8.5/10
Activities and societies: Projects include Support Knowledge Copilot (RAG with verified citations) and a Semantic Cache Gateway for LLM APIs; 2nd Place Augmentix Hackathon (2026), SIH internal qualifier, and 250+ LeetCode/Codeforces problems.
B.Tech in Computer Science Engineering at Bangalore Institute of Technology (CGPA: 8.5/10), graduating June 2027. Built and deployed ML/LLM-based RAG and API-based systems using Python, FastAPI, and Hugging Face.
Availability
Location
Authorized to work in
Job categories
Skills
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