AC

Avi Chauhan

Professional Portfolio

chauhanavi843@gmail.com
5182299998
LinkedIn
GitHub
Portfolio

Skills

Programming Languages

PythonJavaCC++BashRJavaScriptTypeScript

Machine Learning

RegressionClassificationClusteringDecision TreeData PreprocessingData pipelinesModel Training and EvaluationMLOps and MLflowMLOpsMLflow

Deep Learning & Generative AI

PyTorchTensorFlowKerasCNN Model DevelopmentLLM

Natural Language Processing (NLP)

Text PreprocessingNamed Entity Recognition (NER)Sentiment AnalysisTransformersHugging Face

Data Analysis & Visualization

PandasNumPyMatplotlibScikit-LearnPower BIExcel

Computer Vision

Customizing and Fine-Tuning Models for Image Classification

Web Services & Frameworks

Human-Computer InteractionJavaScriptTypeScriptHTML/HTML5CSS/CSS3AjaxReact.jsReact NativeExpress.jsNode.jsVisual Studio CodeReduxNext.jsResponsive designAngularUI/UXNext.js 14/15HTML5CSS3Tailwind CSSShadcn UIRadix UIRESTful APIsWebhooksThird-party API integrations

Tools

GitGitHubMicrosoft Office SuiteDockerOpen-source tools

AWS Services

Amazon SageMakerAWS LambdaAmazon EC2Amazon S3Amazon DynamoDBAmazon CloudWatchSimple Email ServiceEventBridge

Others

Data StructuresAlgorithmsOperating SystemsSystems ProgrammingDatabase System and Database Management: MySQL, SQL ServerAgile MethodologiesDatabase System and Database Management (MySQL, SQL Server)

About

Experienced Software Engineer and Data Analyst with a strong background in machine learning, deep learning, and AI technologies. Skilled in developing end-to-end machine learning pipelines, optimizing AI applications, and implementing data preprocessing techniques. Proficient in a variety of programming languages and frameworks.

Experience

Software Engineering Intern

Silent Infotech Pvt Ltd

January 2024 – April 2024
  • Engineered a production RAG pipeline over 5,000+ internal documents using FastAPI, Sentence Transformers, and hybrid FAISS + BM25 retrieval, serving semantic Q&A to a 20+ engineer team and reducing manual doc lookup time by over 60%.
  • Optimized model serving via ONNX export and INT8 quantization, reducing inference latency by 38% while maintaining accuracy thresholds for production deployment on resource-constrained servers.
  • Designed end-to-end ML pipeline covering ingestion, chunking, embedding, retrieval, and eval, then measured answer relevance using faithfulness scoring and outperformed baseline LLM by 38% on benchmarks.
  • Containerized the full pipeline with Docker and deployed via AWS Lambda + S3, then configured GitHub Actions CI/CD across 4 pipeline stages, reducing release overhead and enabling zero-touch deployments on every merge.

Software Engineering Intern

Opus Technologies

June 2023 – July 2023
  • Fine-tuned VGG-16 on a 100K+ image dataset across 5 disease classes for medical image classification, lifting test accuracy from 71% to 92% by applying targeted augmentation and class-weighting on severely imbalanced data.
  • Developed preprocessing and evaluation pipelines with Pandas, NumPy, and Scikit-Learn, streamlining hyperparameter tuning across 15+ model configurations and reducing experiment cycle time by 3x.
  • Delivered modular Python codebase with documented APIs across 3 classification modules, enabling the team to onboard 2 additional disease datasets with under 4 hours of integration work each.

React Intern

Karvi Engineering & Consultancy

2022 – 2022
  • Actively contributed to multiple live web development projects
  • Focused on building high-quality, responsive web applications
  • Worked extensively with React.js to develop dynamic UI components
  • Ensured cross-browser compatibility and optimal performance
  • Translated client requirements into functional user interfaces

Web Developer Intern

Peace Solutions Private Limited

2021 – 2021
  • Enhanced user experience by incorporating modern design principles
  • Optimized page load times and ensured mobile responsiveness
  • Applied knowledge of building RESTful APIs
  • Ensured seamless data exchange between client and server

Education

Master of Science, Computer and Information Sciences

University at Albany

May 2026

Bachelor of Engineering, Computer Science & Engineering

Indus University

May 2024

Skills

Programming Languages

PythonJavaCC++BashRJavaScriptTypeScript

Machine Learning

RegressionClassificationClusteringDecision TreeData PreprocessingData pipelinesModel Training and EvaluationMLOps and MLflowMLOpsMLflow

Deep Learning & Generative AI

PyTorchTensorFlowKerasCNN Model DevelopmentLLM

Natural Language Processing (NLP)

Text PreprocessingNamed Entity Recognition (NER)Sentiment AnalysisTransformersHugging Face

Data Analysis & Visualization

PandasNumPyMatplotlibScikit-LearnPower BIExcel

Computer Vision

Customizing and Fine-Tuning Models for Image Classification

Web Services & Frameworks

Human-Computer InteractionJavaScriptTypeScriptHTML/HTML5CSS/CSS3AjaxReact.jsReact NativeExpress.jsNode.jsVisual Studio CodeReduxNext.jsResponsive designAngularUI/UXNext.js 14/15HTML5CSS3Tailwind CSSShadcn UIRadix UIRESTful APIsWebhooksThird-party API integrations

Tools

GitGitHubMicrosoft Office SuiteDockerOpen-source tools

AWS Services

Amazon SageMakerAWS LambdaAmazon EC2Amazon S3Amazon DynamoDBAmazon CloudWatchSimple Email ServiceEventBridge

Others

Data StructuresAlgorithmsOperating SystemsSystems ProgrammingDatabase System and Database Management: MySQL, SQL ServerAgile MethodologiesDatabase System and Database Management (MySQL, SQL Server)

Projects

Online Exam Monitoring System

Led as a Scrum Leader of 8 members team in Software Engineering to develop an innovative Online Monitoring Exam System using agile methodology, leveraging Computer Vision, React.js, and Express.js to enhance exam integrity.

React.jsExpress.js

Attendance System

Developed an intelligent Attendance System using Computer Vision and face recognition, seamlessly integrating it with React.js for automated and accurate user identification.

React.js

Machine Learning Model Development for Predictive Analytics

Built models for house price prediction, diabetes classification, and fake news detection using SVM, Logistic Regression, and XGBoost. Employed feature engineering, data pipelines, and model tuning across diverse datasets.

SVMLogistic RegressionXGBoost

FinBridge

FinBridge is a full-stack financial SaaS platform built with Next.js and TypeScript that securely links multiple bank accounts using Plaid and manages user authentication and data storage via Appwrite.

Next.jsTypeScriptPlaidAppwriteChart.jsDwolla

FinVista

FinVista is a full-stack personal finance platform that leverages AI to help you track income, expenses, and budgets effortlessly. Built with Next.js 15 and Prisma, it lets users create multiple accounts, monitor spending patterns, and automate expense categorization via receipt scanning.

Next.jsPrisma

SaaS Learning Management System (LMS)

Built a full-stack SaaS app with Next.js, Supabase, and Stripe, featuring authentication, subscriptions, and AI-powered tutors for interactive learning.

Next.jsSupabaseStripe

Certifications

AWS Certified AI Practitioner (AIF-C01) – Scored 933/1000, Validation No: 5289992c1c274ebeafa5aaddeb0c5d35

© 2026 Avi Chauhan. All rights reserved.