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AI Engineer with less than a year in Computer Vision, GenAI, and MLOps
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AI Engineer Intern with expertise in designing and deploying cloud-native Computer Vision pipelines for smoke study analysis and developing end-to-end AI applications spanning ML, DL, NLP, GenAI, and Agentic AI. Skilled in leveraging AWS services like Lambda and SageMaker for scalable solutions and building robust backend services with FastAPI integrated with React applications. Experienced in owning the complete development lifecycle from model training to production integration, with a strong foundation in data science and machine learning projects.
Vishwakarma Government Engineering College
BE · Computer Science & Engineering (Data Science)
August 1, 2022 – June 30, 2026
Swastik Education Campus(GSEB Board)
HSC
N/A – May 31, 2022
iQudTek
AI Engineer Intern
May 1, 2026 – Present
India
Bacancy Technology
AI/ML Engineer Intern
January 1, 2026 – May 1, 2026
India
RoastForge
June 24, 2026 – Present
Built a 8-node LangGraph + FastMCP agentic workflow that parses resumes, brutally roasts weaknesses, evaluates ATS fit (0–100), iteratively rebuilds until score > 90, generates interview questions, and exports professional PDF resumes autonomously. Integrated Claude Desktop MCP with parallel node execution (Roast + ATS), conditional routing loops, MCP Resources for real PDF delivery, and structured Pydantic outputs; Increased average ATS score from 55 to 84 (+53%) through iterative multi-agent refinement.
View ProjectReal-Time Squid Game (Red Light Green Light)
June 24, 2026 – Present
Built a real-time computer vision game using OpenCV and MediaPipe to detect player movement and enforce "Red Light, Green Light" rules. Implemented pose detection and motion tracking to identify user movements and trigger game logic dynamically. Optimized frame processing for smooth real-time performance.
View ProjectRAG-based YouTube Q&A System
June 24, 2026 – Present
Built a RAG pipeline using LangChain, FAISS, and Gemini to answer questions from video transcripts. Applied chunking and embeddings for efficient retrieval and context-aware responses. Developed a Streamlit interface for real-time querying.
View ProjectCultural Fit Analysis
The candidate's project portfolio showcases a strong interest in cutting-edge AI technologies like agentic AI and RAG systems, aligning well with an innovative and forward-thinking culture. Their experience in both ML/DL and GenAI, coupled with cloud deployment skills, suggests a versatile individual who can contribute across different stages of AI product development. The personal projects indicate a proactive and self-driven learner, which is a positive cultural fit for dynamic environments.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and ownership, as evidenced by independently owning the development lifecycle at iQudTek. Their project descriptions suggest a problem-solving mindset and an ability to integrate various technologies to achieve specific outcomes. The diverse range of projects indicates adaptability and a willingness to explore different AI domains.