CV

Curriculum Vitae of Jha Saket Sunil

Contact Information

Name Jha Saket Sunil
Professional Title Student
Email saketjha0324@gmail.com
Phone +91 9370456334

Professional Summary

This is Saket. I am currently studying at the National Institute of Technology Karnataka (NITK), Mangalore, India. I was born and brought up in Mumbai, Maharashtra, where I spent most of my early years. I am deeply interested in AI & Maths. I enjoy exploring how AI can be used to solve real-world problems, especially in areas like education technology, automation, and large language model applications. I like experimenting with new ideas, building projects, and documenting my learning along the way.

Experience

  • May 2025 - July 2025

    Remote-Hybrid

    AI Engineer Intern
    Kalppo
    • Developed a scalable pipeline using Google Cloud Vision, structured content generation, and fuzzy sequence matching to automate student workbook evaluation, reducing manual assessment time by 80%.
    • Containerized a FastAPI-based REST service for input-driven STEM question and SMILES code generation, featuring a LaTeX-to-image rendering pipeline and Supabase integration for media storage.
    • Collaborated on building an AI-driven Microservice for automated question extraction from PDFs using Mistral OCR, LangChain, and Gemini for structured parsing, with PostgreSQL for metadata storage.

Education

  • 2023 - 2027

    Karnataka, India

    B.Tech
    National Institute of Technology Karnataka, Surathkal
    Civil Engineering, Minor in Information Technology
  • 2021 - 2023

    Dadar, Mumbai

    Junior College
    Kirti M Doongursee College of Arts, Science and Commerce
    12th Science

Awards

  • June
    Winner, Kaggle x Skill Assessment Machine Learning Competition– Rank 1/1846
    Kaggle

Skills

Programming Languages: Python, C++, C, SQL, Bash
Backend & API Development: FastAPI, REST APIs, Async Programming, Pydantic, SQLAlchemy, Alembic
AI / Machine Learning: PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers, OpenCV, SpaCy, DeepEval
LLM & AI Engineering: LangChain, DSPy, Prompt Engineering, RAG Systems, Embeddings, Vector Search
Databases & Vector Stores: PostgreSQL, MySQL, Redis, MinIO, ChromaDB, Vector Databases
Cloud & DevOps: Docker, Kubernetes, Google Cloud Platform (GCP), CI/CD, MLflow
Developer Tools: Git, Linux, Bash, Jupyter Notebook, VS Code
Data Science & Analytics: Pandas, NumPy, Data Processing, Feature Engineering, Model Evaluation
Systems & Performance Engineering: Parallel Computing, Multithreading, Graph Algorithms, High Performance Computing
Computer Vision: OpenCV, Image Processing, Object Detection, Video Analysis

Languages

Hindi : Native speaker
English : Fluent
Marathi : Fluent

Interests

Watching Sports: Cricket, Football, Tennis, Esports
Gaming: BGMI, Valorant, Clash of Clans, Call of Duty, PC Games, Horror Games, Mystery Games, Puzzle Games, Story-driven Games

Certificates

Projects

  • FileForge

    A distributed file storage system enabling secure file and folder management with scalable backend architecture.

    • Built a distributed file storage system supporting nested folders, uploads, ZIP extraction, and favorites.
    • Implemented secure authentication and session management using JWT and OAuth2.
    • Integrated MinIO object storage with PostgreSQL metadata storage and optimized indexing.
    • Achieved ~40% faster file metadata queries with optimized database design.
    • Designed modular FastAPI routes and containerized deployment using Docker.
  • Paragon

    Developed PARAGON, a high-performance parallel graph processing library featuring a C++ computational core with Python bindings, published as a Python package while maintaining performance critical logic in C++.

    • Built using C++, Python, CMake, OpenMP, and pybind11, implementing parallel graph algorithms including PageRank, SSSP, and Triangle Counting with optimized data structures and thread level parallelism.
    • Benchmarked against sequential implementations, achieving up to 80× speedup in SSSP, 3.4× in Triangle Counting, and 2.5× in PageRank on multicore CPUs.
  • ATLAS – Adaptive Traffic Light Allocation System

    A computer vision based adaptive traffic signal system that dynamically allocates signal timings using real-time vehicle detection and tracking.

    • Developed real-time vehicle detection and tracking using YOLOv8 and ByteTrack.
    • Implemented Region Masking and frame-based confirmation filtering for accurate vehicle counting.
    • Designed DBWSA algorithm to dynamically allocate green signal time based on vehicle density and class.
    • Achieved 25% average and 50% peak efficiency improvements over fixed traffic signals across 500+ simulations.
    • Built a flexible pipeline supporting multi-source video input, YAML configuration, and Pydantic validation.
  • FilmFusion

    A hybrid movie recommendation system combining semantic embeddings with content-based filtering.

    • Implemented hybrid recommendation using Sentence Transformers and semantic similarity.
    • Used FAISS vector indexing for efficient embedding search and retrieval.
    • Enabled dynamic filtering by genre, language, popularity, runtime, and release year.
    • Built an interactive web interface using Streamlit.

Extracurricular Activities

  • Web Club NITK — Member
    • Organized Silicon Maze, Web Club’s flagship event, successfully coordinating 500+ online participants.
    • Conducted session on Mamba SSM , highlighting its architecture and advantages for efficient sequence modeling.