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AI Engineer with 1+ years in Generative AI, NLP, and Distributed Systems.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Second-year B.Tech student specializing in Machine Learning, Generative AI, and backend systems, with hands-on experience building multi-agent RAG pipelines, autonomous AI frameworks, and production-grade ML applications. Actively seeking an AI/ML or Generative AI internship to apply research-driven engineering skills to real-world problems.
Maharaja Agrasen Institute of Technology (GGSIPU)
B.Tech · Computer Science & Engineering
August 1, 2024 – June 30, 2028
BYTE Society
Backend & ML Developer
September 1, 2024 – Present
India
Devlens
March 1, 2026 – Present
1. Built an AI codebase navigator using deterministic AST parsing and hybrid vector search, mapping 500+ code dependencies and GitHub issues across multi-language repositories. 2. Engineered a transformer-based agentic backend with multi-lingual, stateless context injection to explain architectural intent using OpenRouter and LLMs, reducing onboarding time by ~60%.
View ProjectJal Drishti
January 1, 2026 – Present
1. Architected a real-time computer vision underwater surveillance system using YOLOv8 and FUnIE-GAN, achieving 89%+ mAP on threat detection across 5 object classes. 2. Designed a dual-mode backend leveraging WebSockets for low-latency (<80ms) telemetry and multi-stream video processing.
View ProjectDebateMind
November 1, 2025 – Present
1. Engineered an autonomous AI debate framework using Reinforcement Learning to optimise LLM reasoning, backed by a real-time RAG pipeline for semantic recall and fact-checking.
View ProjectData Wiping Tool (DropDrive)
September 1, 2025 – Present
1. Developed a MERN stack data-wiping application with C++ logic implementing secure NIST SP 800-88 standards; shortlisted in Smart India Hackathon (SIH).
View ProjectClauseCraft AI
August 1, 2025 – Present
1. Built a multi-agent AI policy navigator using retrieval-augmented generation (RAG) and a deterministic NLP validation engine, reducing manual eligibility-check time by ~70% and processing 10+ policy documents simultaneously.
View ProjectMachine Learning Specialization
Deeplearning.ai
February 1, 2026 – Present
Generative AI with LLMs
Deeplearning.ai
December 1, 2025 – Present
CS50P - Programming with Python
Harvard University
December 1, 2024 – Present
Cultural Fit Analysis
The candidate exhibits a strong cultural fit for an AI Engineer role, particularly in an innovative and fast-paced environment. Their diverse range of personal projects, covering computer vision, NLP, RAG, and reinforcement learning, demonstrates a proactive and self-driven learning attitude. Involvement in hackathons and leadership roles within a technical society indicates a collaborative spirit and a willingness to contribute beyond core responsibilities. The candidate's stated goal of applying 'research-driven engineering skills to real-world problems' aligns well with a product-focused AI team. The breadth of skills and technologies used across projects suggests adaptability and a strong desire to explore new domains within AI.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative, leadership, and collaboration skills through their involvement in BYTE Society and spearheading technical events. Their project descriptions indicate an ability to work on complex, multi-faceted problems and deliver tangible results (e.g., reducing onboarding time, improving mAP). The focus on real-world problem-solving in projects like 'Jal Drishti' and 'ClauseCraft AI' suggests a practical and results-oriented approach. The candidate's academic background and certifications further support a strong learning aptitude and dedication to continuous skill development.