AI Engineer with less than a year in Deep Learning, Computer Vision & LLM Applications
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Highly motivated M.Tech student in Robotics & Artificial Intelligence with a strong foundation in machine learning, deep learning, and LLM applications. Experienced in developing AI solutions for image captioning, text-to-image generation, face tracking, and RAG-based chatbots. Proficient in Python, PyTorch, TensorFlow, and AWS, I am seeking to apply my skills in an challenging AI Engineering role.
Indian Institute of Technology, Guwahati
M.Tech · Robotics & Artificial Intelligence
August 1, 2024 – Present
Jorhat Engineering College
B.Tech · Computer Science & Engineering
August 1, 2019 – June 30, 2023
AHSEC Board
Senior Secondary
N/A – May 31, 2019
SEBA Board
Secondary
N/A – May 31, 2016
Indian Institute of Technology, Guwahati
Intern
July 1, 2021 – September 1, 2021
Guwahati, Assam, India
Medical Chatbot with RAG, LangChain, Pinecone, Flask, and AWS
September 1, 2025 – October 1, 2025
RAG medical QA chatbot served via Flask; used Ollama Llama 3 for low-cost local inference. Dockerized the app and set up CI/CD using GitHub Actions, Amazon ECR, and an EC2 self-hosted runner. Hardened AWS setup (VPC/security groups, env configs) for secure public access.
View ProjectFace Search & Multi-Face Tracking in Crowded Videos (Master's Thesis)
August 1, 2025 – Present
Trained ShuffleFaceNet on CASIA-WebFace to generate l2-normalized face embeddings and implemented KD-tree top-k similarity search for efficient face retrieval. Integrated RetinaFace for face detection and developed crowded-scene multi-face tracking using DeepSORT / FaceQSORT with OpenCV and PyTorch.
View ProjectAttnGAN (TensorFlow): Text-to-Image on CUB-200-2011
August 1, 2024 – October 1, 2024
Implemented an Attentional GAN with word-level attention; trained and tested on CUB-200-2011 via CLI. Organized the birds dataset with caption pickles and exported epoch-wise sample grids for qualitative checks. Proposed a StyleAttnGAN extension that adds style-aware attention and a style loss to improve image coherence.
View ProjectCultural Fit Analysis
The candidate's academic background from a reputable institution (IIT Guwahati) and diverse project portfolio (personal, academic, thesis) suggest a strong drive for learning and application. The projects cover various AI sub-fields, indicating adaptability and a broad interest in the domain. The experience with CI/CD and AWS also shows an understanding of modern development practices, which aligns well with a collaborative, engineering-focused culture.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a structured approach to problem-solving and an understanding of deployment considerations (CI/CD, AWS hardening). The academic background suggests a capacity for rigorous technical work. However, without direct interview data, soft skills like teamwork, communication, and adaptability cannot be fully assessed.