I am Pranav Samadhan Khaire, a B.Tech (Computer Science and Design) student at MIT, Chhatrapati Sambhaji Nagar, building practical AI systems with strong software engineering fundamentals.
My work sits at the intersection of Machine Learning, Agentic AI, Automation, and Full-Stack Product Engineering. I focus on building systems that are not only intelligent, but also stable, maintainable, and usable in real workflows.
| Category | Details |
|---|---|
| Role | AI/ML Engineer in Training, Full-Stack Builder |
| Education | B.Tech in Computer Science and Design (2nd Year) |
| Primary Specialization | Agentic AI, LangChain Agents, Workflow Automation |
| Secondary Specialization | Data Science, Backend APIs, Mobile Integration |
| Tools-First Mindset | Build reusable modules, automations, and deployment-ready systems |
| Current Objective | Internship and collaboration in AI product engineering |
AI & Machine Learning Intern | 12 January 2026 β 12 March 2026
- Built an AI-powered student mentoring intelligence system (HEPro AI+).
- Developed algorithms for academic, wellness, productivity, and career readiness scoring.
- Applied machine learning (K-Means Clustering) for student segmentation and behavioral analysis.
- Designed mentor recommendation and intervention logic using Python, Pandas, Scikit-learn, and Data Analytics.
AI & Machine Learning Intern | 2026
- Focused on practical implementation and hands-on project-based learning.
- Developed industry-oriented AI/ML skills aligned with professional standards.
- Strengthened knowledge of machine learning concepts, analytical thinking, and practical software development.
- Design and implement LangChain agent pipelines with tool usage and chaining.
- Build multi-step reasoning workflows for planning, execution, and decision support.
- Integrate agents with APIs, data stores, and backend services.
- Structure prompt and memory strategies for consistent and controlled outputs.
- Create practical assistants for analytics, recommendations, and productivity automation.
- Develop Python automation scripts for repetitive technical workflows.
- Build API-connected orchestration pipelines for data movement and task execution.
- Create automations for reporting, scheduling, and operational efficiency.
- Design reusable automation modules with clear inputs, outputs, and monitoring.
- Improve reliability through modular logic and testable flow design.
- Work with mobile-first application design and backend-aware feature planning.
- Understand Android APK lifecycle: build, package, version, and release readiness.
- Integrate mobile clients with APIs for authentication, data sync, and service calls.
- Bridge AI/ML features into mobile-oriented product workflows.
- Drive prototype-to-release discipline with practical engineering checkpoints.
- Build end-to-end ML pipelines: preprocessing, feature engineering, training, evaluation.
- Use NumPy, Pandas, scikit-learn, Matplotlib for data-driven model development.
- Apply NLP foundations to language-centric applications and recommendation use cases.
- Connect model outputs to real interfaces and business logic.
- Prioritize explainability, reproducibility, and meaningful performance metrics.
- Build Flask REST APIs with modular architecture and clean routing.
- Deliver responsive frontends using HTML, CSS, JavaScript, Tailwind CSS, React, Vite.
- Work with MongoDB, MySQL, SQLite for structured and semi-structured data.
- Implement integration-ready systems from frontend to backend to database.
- Focus on security basics, API consistency, and maintainable code structure.
flowchart LR
A[Problem Definition] --> B[Data Collection & Validation]
B --> C[Model or Logic Design]
C --> D[Agentic Workflow or Automation Pipeline]
D --> E[API Integration]
E --> F[Web or Mobile Interface]
F --> G[Testing and Iteration]
G --> H[Deployment and Monitoring]
I follow a system-first approach where AI is one layer of the solution, not the entire solution.
| Domain | Practical Depth | Tools and Frameworks | Delivery Outcome |
|---|---|---|---|
| Agentic AI | Multi-step agents, tool chaining, retrieval-aware orchestration | LangChain, Python, API integrations | Intelligent assistants and automated decision flows |
| Automation | Workflow scripting, API process orchestration, repeatable pipelines | Python, REST APIs, schedulers, structured scripts | Time-saving production automations |
| Mobile APK Workflows | Build/package understanding, backend integration, service-driven features | Android APK process, API layer integration | Mobile-ready AI-enabled application flows |
| ML Engineering | Data pipelines, model evaluation, visualization, feature processing | NumPy, Pandas, scikit-learn, Matplotlib | Predictive and recommendation modules |
| Backend Engineering | API design, routing, integration patterns, data handling | Flask, REST, MongoDB, MySQL, SQLite | Reliable backend services |
| Full-Stack Product Delivery | UI + API + data synchronization | JavaScript, React, Tailwind CSS, Flask stack | Deployable end-to-end products |
| DevOps Foundations | Containerization and CI fundamentals | Docker, GitHub Actions | Reproducible builds and streamlined deployment |
Here is a quick overview of my core technical strengths based on my project experience:
- Frontend Development: HTML, CSS, JavaScript, Tailwind CSS, UI Components, Responsive Design
- Backend & System Development: Python, Flask, API Design, Authentication Systems
- Data Science & Analysis: NumPy, Pandas, Matplotlib, Data Cleaning & Preprocessing
- AI & Machine Learning: ML Models, Deep Learning, Neural Networks, AI Algorithms
- UI/UX & Visual Design: UI/UX Principles, Wireframes, Prototypes, Visual Design
- Git, GitHub & Deployment: Git, GitHub, Cloud Infrastructure, Project Deployment
Purpose: Environmental monitoring, reporting, and verification workflow support. Engineering Work: Structured data processing, geospatial data interpretation, and workflow clarity for monitoring tasks.
Purpose: Internship matching and allocation assistance system. Engineering Work: Full-stack workflow, database-backed candidate/internship data handling, and allocation logic.
Purpose: Multi-agent collaborative intelligence system for complex task processing. Engineering Work: Agentic architecture, tool chaining, and automated decision flows.
Purpose: AI-powered skill and learning recommendation system. Engineering Work: Recommendation logic, ML-driven guidance, and user-facing output design.
Purpose: AI-driven healthcare insights and analysis. Engineering Work: Deep learning models for medical data, integrated with a secure backend.
Purpose: Sustainability tracking and carbon footprint reduction platform. Engineering Work: Data analytics, full-stack implementation, and predictive modeling for emission reduction.
Purpose: Comprehensive health tracking and predictive diagnostic tool. Engineering Work: Health data aggregation, predictive ML algorithms, and intuitive frontend dashboard.
Purpose: Digital platform concept for agriculture connectivity and service access. Engineering Work: End-to-end full-stack integration with backend service logic for agricultural workflows.
- Winner (Sharkpreneur): ZENTRIX'26 Pitch Competition (Mar 2026)
- 1st Prize: Lightning Pitch 2026 (Feb 2026)
- 1st Prize: Cogni-Sphere 2025 (IETE, MIT CSN, Oct 2025)
- 2nd Prize: SANKALPANA 2025 (District Level, Nov 2025)
- Runner-Up: Honeywell Sustainability Innovation Challenge (Mar 2026)
- State Level Finalist: DIPEX 2026 Working Model Exhibition (Mar 2026)
- Qualified Round 1: Build for Bharat National Innovation Hackathon (Apr 2026)
- Participant: HackSphere 2025, HackFusion 3, IGNITION 2K26, IDE Bootcamp, IDEATHON 9.0, Government College Ideathon.
- 30+ certifications and badges across Microsoft, Oracle, Google Cloud, TCS iON, HCL, IBM, Simplilearn, HP LIFE, and others.
- 12+ completed projects across AI/ML, web platforms, and full-stack systems.
- Oracle Fusion Cloud Applications CX Process Essentials Certified
- Oracle Certification
- TCS iON Career Edge - IT Primer
- Microsoft Skill India Certification
- AICTE IDE Bootcamp Certificate
- Smart India Hackathon Participation
- Wadhwani Bootcamp Certificate
- Zomato Hackathon Participation
- NSUT Certificate
- Advanced data science workflows and robust model evaluation.
- Agentic AI architecture using LangChain and tool ecosystems.
- Reliable automation systems for real operational use.
- Deployment discipline aligned with MLOps principles.
- Mobile + backend integration with APK-ready release practices.
- Problem-first engineering: Start from user needs and measurable goals.
- Reliability over hype: Build maintainable systems with consistent behavior.
- Execution quality: Design modular code and reusable architecture.
- Continuous growth: Learn fast, ship often, improve based on evidence.
- Ownership mindset: Communicate clearly and deliver accountable results.
- Portfolio: https://pranav-portfolio-nine-theta.vercel.app/
- LinkedIn: https://www.linkedin.com/in/pranav-khaire-732793338
- GitHub: https://github.com/pranav16-king
- Email: mailto:pranavkhaire53@gmail.com
- Twitter/X: https://twitter.com/pranavkhaire16
- Instagram: https://www.instagram.com/pranav_khaire___/
Building consistent systems. Solving practical problems. Growing with every release.