AI Resume Screening
An AI-powered resume analysis and ranking system combining semantic similarity with LLM-based information extraction.
Hybrid semantic + structured scoring approach.
- Python
- FastAPI
- React
- Sentence Transformers
- MiniLM
- +3
Utkarsh Srivastava
AI/ML Engineer|Computer Science Student
Building intelligent systems through machine learning, deep learning, and modern AI engineering.
I'm a B.Tech Computer Science student focused on machine learning, deep learning and generative AI. My work spans model training and evaluation, retrieval-augmented generation and LLM applications, computer vision, and the backend/API layer that turns a model into a usable product.
AI/ML
Machine Learning & Deep Learning
Projects
Multiple End-to-End AI Systems
Focus
AI Engineering & Generative AI
Education
B.Tech Computer Science
01 / About
About Me
I'm a B.Tech Computer Science student specializing in AI/ML, interested in building practical intelligent systems rather than notebooks that never leave the laptop.
My focus areas are machine learning, deep learning, NLP, computer vision, LLMs and RAG — paired with the AI engineering and backend work needed to serve them: FastAPI services, clean data pipelines, and honest evaluation.
Currently exploring
- LangChain
- LangGraph
- RAG systems
- LLM evaluation
- AI agents
02 / Projects
Featured Projects
End-to-end systems — each one has a problem, an architecture and a working implementation. Open a case study for the full pipeline.
VisionSpeak
A computer vision and image understanding system that turns what the camera sees into spoken natural language.
Vision-to-language pipeline built for real-time use.
- Python
- OpenCV
- PyTorch
- Vision Models
- Text-to-Speech
Driver Drowsiness Detection
A real-time computer vision system that detects driver drowsiness from a webcam feed and raises an alert.
Real-time detection with a temporal window to suppress false alarms.
- Python
- OpenCV
- TensorFlow
- CNN
- Real-Time Inference
ResearchPilot AI
An AI-powered research assistant built around advanced RAG, agentic workflows, evaluation, and production AI engineering.
Advanced RAG and production AI engineering in one research assistant.
- Python
- RAG
- LangChain
- LangGraph
- LLM Evaluation
- +2
03 / Skills
Technical Skills
Tools and concepts I actively use across modelling, generative AI, vision and the backend layer.
Programming
- Python
- Java
- C
- SQL
Machine Learning
- Scikit-learn
- Feature Engineering
- Model Evaluation
- Supervised Learning
- Unsupervised Learning
Deep Learning
- PyTorch
- TensorFlow
- CNNs
- RNNs
- LSTMs
- Attention Mechanisms
Generative AI
- LLMs
- RAG
- Embeddings
- Vector Databases
- Prompt Engineering
- LangChain
- LangGraph
Computer Vision
- OpenCV
- Image Classification
- Image Captioning
- Object Detection
Backend / Development
- FastAPI
- REST APIs
- React
- Git
- GitHub
04 / Journey
Learning Journey
A progression rather than a job history — how the computer science foundation turned into AI engineering work.
Foundation
B.Tech Computer Science — DIT University
Core computer science coursework building the systems foundation everything else sits on.
- Data Structures & Algorithms
- DBMS
- Operating Systems
- Computer Networks
- Computer Organization
- Compiler Design
- Theory of Computation
Step 01
Machine Learning
Supervised and unsupervised learning, feature engineering, and honest model evaluation with Scikit-learn.
- Scikit-learn
- Feature Engineering
- Model Evaluation
Step 02
Deep Learning
Neural network architectures in PyTorch and TensorFlow — CNNs for vision, RNNs/LSTMs and attention for sequences.
- PyTorch
- TensorFlow
- CNNs
- LSTMs
- Attention
Step 03
Generative AI
LLM applications, embeddings and vector search, retrieval-augmented generation, and prompt design.
- LLMs
- RAG
- Embeddings
- Vector Databases
Now
AI Engineering
Shipping models as services: FastAPI backends, evaluation loops, agent workflows with LangChain and LangGraph.
- FastAPI
- LangChain
- LangGraph
- LLM Evaluation
05 / Achievements
Achievements
Hackathon Participation
Amazon ML challenge · [2025]
Built and presented working prototypes under time constraints.
ML Competitions
Predicting Smartphone Addiction · Kaggle
Participated in applied machine learning competitions.
Coding Practice
LeetCode
Consistent data structures and algorithms practice.
Academic
Vibe Coding Challenge · 2025
Runner-Up in a coding challenge hosted by Technical club.
06 / Blogs
Blogs
Writing on AI engineering, machine learning systems, and the practical lessons behind the projects.
- Machine Learning
Demystifying Principal Component Analysis (PCA): A Step-by-Step Mathematical Formulation
A clear walkthrough of PCA from covariance construction to eigen decomposition, with the mathematical intuition needed to use it confidently.
Aug 11, 2025Read - Large Language Models
The Rise of Efficient AI
An opinionated take on why compact models are closing the gap with giant systems and where efficient AI can outperform brute force scale.
Jan 31, 2026Read - RAG
How RAG Actually works: From Embeddings to Retrieval
An upcoming practical guide to the full RAG flow: chunking, embeddings, vector indexing, retrieval, reranking, and grounded generation.
UpcomingComing soon
07 / Education
Education
DIT University
B.Tech, Computer Science & Engineering
AI/ML specialization
Relevant coursework
- Data Structures & Algorithms
- DBMS
- Operating Systems
- Computer Networks
- Computer Organization
- Compiler Design
- Theory of Computation
- Machine Learning
Want the complete picture?
View or download my resume for a detailed overview of my projects, technical skills, and experience.
08 / Contact
Let's Build Something Intelligent
Open to internships, AI/ML roles and collaboration on applied machine learning projects.