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AI/ML Intern with less than a year in RAG systems & multilingual NLP pipelines.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Final-year Computer Science undergraduate specializing in AI & ML with experience in RAG systems, multilingual NLP pipelines, agentic AI workflows, LLM-powered translation, prompt engineering, and Pinecone vector retrieval systems.
Vellore Institute of Technology
Bachelor of Technology · Computer Science & Engineering
September 1, 2022 – Present
Greynium Technologies (OneIndia)
AI/ML Intern
January 1, 2026 – Present
Bengaluru, Karnataka, India
Yectra Technologies
Front-End Intern
May 1, 2025 – June 1, 2025
Coimbatore, Tamil Nadu, India
Agentic AI Email Triage Assistant
May 1, 2026 – June 1, 2026
Built an autonomous email agent that classifies, drafts, and schedules on behalf of the user, reducing inbox handling time by an estimated 60-70% by triaging emails into respond/schedule/FYI/escalate categories. Designed a multi-step agent loop using Composio's MCP toolset for Gmail and Google Calendar integration, with tool-whitelisting in code to enforce drafts-only mode and prevent unauthorized actions. Prepared a voice-cloning module that profiles the user's writing style from 200+ sent emails and a sensitivity gate that escalates emotionally or financially sensitive messages before drafting. Built a FastAPI review UI with full audit logging in MongoDB and an eval harness measuring classification accuracy, escalation precision/recall, and draft quality via LLM-as-judge across 100+ labeled examples.
QFE-COD: Quantum-Enhanced Camouflaged Object Detection
January 1, 2026 – April 1, 2026
Architected a hybrid quantum-classical object detection framework integrating PVTv2 transformers, HQCM circuits, and Q-WaveKAN modules for COD10K-v3 containing 10K+ camouflage images. Formulated a two-stage CAM/NonCAM classification and segmentation pipeline, improving inference efficiency by 18% while significantly reducing false-positive detections. Integrated Frequency Self-Attention, Dual-Domain Fusion, and Mamba-inspired FPN decoders to model spatial and inter-frequency dependencies effectively. Achieved 94.23% CAM classification accuracy with 0.7889 Dice and 0.7402 IoU on COD10K-v3, surpassing SINetV2 by 14.83% Dice score.
AWS Certified Cloud Practitioner
AWS
June 1, 2026 – Present
AWS Academy Cloud Foundations
AWS Academy
June 1, 2026 – Present
Python Essential Training
Unknown
June 1, 2026 – Present
AWS Educate
AWS
June 1, 2026 – Present
Introduction to Generative AI
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects and internships demonstrate a strong interest and practical application in AI/ML, aligning well with an AI/ML Engineer Intern role. The diversity of projects, from agentic email assistants to quantum-enhanced object detection and multilingual NLP, indicates a broad curiosity and willingness to explore different facets of AI. The experience with various tools and frameworks suggests adaptability. However, the experience level is still early career, and cultural fit would need to be further assessed through behavioral interviews.
Soft Skills & Operational Fit
The candidate's project descriptions indicate strong problem-solving skills and an ability to work on complex, multi-faceted problems. The internship experience at Greynium Technologies suggests an ability to integrate into a team and contribute to production-level systems. The detailed descriptions of methodologies and results in projects imply a structured approach to development and a focus on measurable outcomes. However, without direct assessment data, specific soft skills like teamwork, communication, and stress handling cannot be definitively evaluated.