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AI Engineer with less than a year in Machine Learning & AWS
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Computer Science graduate with practical experience in deploying ML models using AWS SageMaker, building NLP and summarization tools with Google Gemini API, and analyzing data using Python. Skilled in TensorFlow, PyTorch, and data pipeline development. Completed internship with real AWS deployment experience and led multiple data-driven academic projects.
Chalapathi Institute Of Engineering And Technology
BTech · Computer science and Engineering
August 1, 2020 – April 19, 2024
Noble Sai Junior College
Intermediate
June 1, 2018 – May 31, 2020
ZP High School
SSC
June 1, 2017 – May 31, 2018
AICTE Eduskills | AWS Academy
AI/ML Virtual Intern
May 1, 2023 – July 1, 2023
India
AI-Powered Chat, Web & YouTube Summarization Tool
April 1, 2024 – June 1, 2026
Designed an AI-powered summarization pipeline using Gemini API, Whisper, DuckDuckGo and RAG for fast content analysis, automating video and web summarization in under 5 seconds and reducing manual review time by 70% extraction. Summarized 10+ websites and YouTube videos (10 mins each) in <5 seconds using Python and Flask APIs. Improved productivity by 70% by reducing content review time through automated, structured summaries. Integrated RAG with Vector DBs to enable PDF/document upload and intelligent Q&A, allowing users to query specific sections of content.
AI-Thalli: Voice-Based Smart Assistant App (Flutter + FastAPI + Gemini AI)
April 1, 2024 – June 1, 2026
Built a personal voice assistant app that understands natural speech and performs actions like booking rides, opening apps, ordering food, and answering questions in real time. Integrated Speech-to-Text, Text-to-Speech, and Gemini AI to understand intent and respond naturally. Implemented 3 UI themes: Dark, Light, and Transparent. The Transparent mode allows users to set custom wallpapers for a personalized interface. Used Kotlin AccessibilityService to automate app interactions (e.g., Rapido, Uber, Zomato, Zepto). Reduced manual steps by 85% and enabled smooth hands-free task completion.
Data Science & Machine Learning
Cranes Varsity, Bengaluru
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects show a strong interest in practical AI applications and innovation, which aligns well with a dynamic, tech-driven environment. The diversity of projects (summarization, voice assistant) and the use of various tools (AWS, Gemini API, Flutter, FastAPI) indicate adaptability and a willingness to learn new technologies. The internship experience with AWS Academy suggests a proactive approach to gaining industry-relevant skills. The focus on efficiency and automation in projects also points to a good fit for roles valuing impact and optimization.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving and efficiency improvements (e.g., 'reducing manual review time by 70%', 'reduced manual steps by 85%'), suggesting a results-oriented approach. The academic projects demonstrate initiative and the ability to work on complex, multi-component systems. However, without direct interview data, assessing collaboration, stress handling, or specific work attitude is not possible.