AI Engineer with less than a year in Deep Learning, RAG, and Computer Vision.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer (Fresher) with skills in Python, Deep Learning & RAG. Proficient in TensorFlow, Keras, scikit-learn & LangChain for model development and deployment.
University BDT College of Engineering, Davanagere
Bachelor of Engineering · Computer Science
August 1, 2022 – June 30, 2026
Sri Siddeshwara PU College, Davanagere
Pre University
June 1, 2020 – May 31, 2022
Sri Someshwara Vidyalaya, Davanagere
SSLC
June 1, 2019 – May 31, 2020
YouTube Video Q&A System using RAG
June 1, 2026 – Present
Built a Retrieval-Augmented Generation (RAG) system to enable contextual Q&A over YouTube transcripts using embeddings and LLMs. Implemented text chunking, and a Streamlit UI for real-time querying and summarization (without conversational memory).
Women Safety Mobile Application
June 1, 2026 – Present
Built an Android application providing real-time safety alerts and emergency location sharing for women.
Melanoma Detection Model
June 1, 2026 – Present
Trained a CNN to classify skin images (benign vs. malignant) with 91% accuracy; improved generalization using data augmentation and implemented Grad-CAM visual explanations in a Streamlit demo for real-time interpretability.
Multi-Source AI Research Agent
June 1, 2026 – Present
Built an agentic AI research system using LangGraph that allows users to choose web or YouTube research, automates information retrieval and analysis through LLMs, extracts video knowledge via transcripts, and generates optimized research reports using evaluation loops.
GenAI Powered Data Analytics Job Simulation
Tata Forage
January 1, 2025 – Present
Machine Learning Using Python
Simplilearn
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest in cutting-edge AI technologies (RAG, agentic AI, interpretability) and a proactive approach to learning new frameworks (LangGraph, Streamlit). The diversity of projects, from mobile safety to melanoma detection, indicates a broad interest in applying AI to various domains. This aligns well with a culture that values innovation, continuous learning, and practical application of AI, which is typical for an AI Engineer role. However, all projects are academic, so experience in a professional team environment is not evident.
Soft Skills & Operational Fit
The candidate lists analytical thinking, problem-solving, curiosity, and communication as soft skills. The project descriptions indicate an ability to apply these in practical scenarios, particularly in problem definition and solution implementation for AI/ML tasks. However, without direct interview data, the depth of these skills in a collaborative or high-pressure operational environment cannot be fully assessed.