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AI Engineer with less than a year in Machine Learning & Deep Learning
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Final-year Computer Science student specialising in machine learning, deep learning, and author of a government-funded deepfake detection system leveraging ResNet, LSTM, and Transformer architectures for computer vision tasks. Seeking an entry-level AI/ML or software engineering role to deliver immediate impact.
Canara Engineering College, Bantwal (VTU)
BE · Computer Science & Business Systems
August 1, 2022 – June 30, 2026
St. Aloysius PU College, Mangalore
Class XII
June 1, 2020 – May 31, 2022
Shree Narayanguru EM School, Mangalore
Class X
June 1, 2019 – May 31, 2020
MindMatrix.io
Android App Development using Generative AI
February 1, 2026 – May 1, 2026
India
Resume Screening Assistant
November 1, 2025 – December 1, 2025
Built a multi-agent LLM application using LangGraph orchestration and Groq's inference API to score resumes against job descriptions across Skills, Experience, Education, and Extras dimensions. Applied Retrieval-Augmented Generation (RAG) to ground scoring in JD context, reducing hallucination and improving recommendation accuracy. Automated first-pass shortlisting for multiple roles simultaneously, cutting estimated manual screening effort by 70%.
Deepfake Detection System [KSCST Govt. Funded]
January 1, 2025 – December 1, 2025
Designed a multimodal deepfake detection pipeline combining ResNet (spatial features), LSTM (temporal modelling), and Vision Transformer architectures, achieving 73%+ detection accuracy on the FaceForensics++ benchmark. Built end-to-end ML pipeline covering data augmentation, transfer learning fine-tuning, model evaluation, and a React.js dashboard for real-time inference via REST API. Awarded KSCST government funding one of the few undergraduate projects selected state-wide by the Karnataka State Council for Science and Technology.
View ProjectAI-Generated Text Detection
January 1, 2024 – March 1, 2024
Fine-tuned RoBERTa on a labelled corpus of human-written and AI-generated text, reaching 89% F1-score on held-out test data. Engineered NLP features (perplexity, burstiness, n-gram entropy) to improve model interpretability and classification explainability.
Foundations of AI and Machine Learning
Microsoft (Coursera)
March 1, 2026 – Present
Introduction to AI
Google (Coursera)
March 1, 2026 – Present
Java Programming
Scaler
August 1, 2025 – Present
Mobile App Development with Flutter
Workshop
November 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from deepfake detection to resume screening and AI-generated text detection, shows a broad interest in AI applications. The academic and personal projects, especially the government-funded one, indicate a proactive and innovative mindset. The target role of 'AI Engineer' aligns well with the candidate's demonstrated skills and project focus. The Android development internship, while not directly AI-focused, shows versatility and an ability to learn and apply new technologies, which is a positive indicator for adaptability within a team.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations (e.g., multimodal deepfake detection, multi-agent LLM application). The internship experience highlights an ability to work independently and deliver a full-stack application, indicating good self-management and project ownership. The KSCST grant achievement suggests initiative and the ability to secure external validation for technical work. The VTU Basketball Representative achievement indicates teamwork and leadership potential.