ML undergrad and freshie
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
ai-driven-technical-interviewer
January 10, 2026 – Present
AI-powered multimodal technical interviewer with adaptive questioning and automated evaluation
View Projectagentic-hr-ai
January 8, 2026 – Present
Agentic HR chatbot using RAG, FAISS, and LLM APIs with Dockerized deployment
View Projectchatbot_sentiment_analysis
November 24, 2025 – November 25, 2025
chatbot_sentiment_analysis — GitHub repository
View ProjectGenerative-Content-Variant-Engine
October 31, 2025 – October 31, 2025
> Modular FastAPI-based system for generating personalized content variants from base templates using LLMs and emotion-tone conditioning. Demonstrates scalable prompt, image, and mood-based generation pipelines with mocked DB and storage integrations for safe, reproducible experimentation.
View Projectincois_api_test_2
November 12, 2024 – November 12, 2024
incois_api_test_2 — GitHub repository
View Projectincois_api_test_1
November 12, 2024 – November 12, 2024
incois_api_test_1 — GitHub repository
View ProjectSAR-Colorization-ISRO
September 20, 2024 – October 7, 2024
This project focuses on colorizing grayscale Synthetic Aperture Radar (SAR) images using Deep Learning models trained on paired SAR and Optical data. The goal is to improve SAR data interpretability for geological and environmental applications by predicting natural colors, enhancing visual analysis and insights.
View ProjectRAGs-vs-Fine-tuning
August 8, 2024 – September 20, 2024
This project explores the performance of Retrieval-Augmented Generation (RAG) and fine-tuned GPT-2 models on the Stanford Question Answering Dataset (SQuAD). The goal is to compare the results of RAG and GPT-2 in answering questions based on the provided context.
View ProjectResearch-Paper-LLM-
June 27, 2024 – August 18, 2024
This is a LLM using the Transformer Architecture with self defined attention heads with the help of PyTorch. This code is a companion to the research paper written by me on the Impact of Transformers in NLP Tasks.
View ProjectCultural Fit Analysis
The candidate demonstrates a strong interest in cutting-edge AI/ML technologies, particularly LLMs, which aligns well with a forward-thinking, research-oriented culture. The breadth of personal projects, from AI interviewers to SAR image colorization, suggests a curious and versatile individual. However, the lack of team projects or formal work experience makes it challenging to fully assess cultural fit in a collaborative professional environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and experimental approach to problem-solving, which aligns with an innovative operational environment. The diversity of personal projects suggests self-motivation and a continuous learning mindset. However, without formal work experience or psychometric test results, it's difficult to assess collaboration, stress handling, or communication clarity in a team setting.