Machine Learning Engineer - MLOps & Web AI

+91-931******* ****************@*****.*** LinkedIn GitHub

Novel Evaluation of Large Language Models via a Synthetic Conlang Benchmark (Under Review) Samsung Innovation Campus — Artificial Intelligence 2026 IBM SkillsBuild — Generative AI & Cloud Computing 2026 Visa Petition Approval Prediction Github

CatBoost, XGBoost, FastAPI, SHAP, MLflow, Evidently AI Developed ML classifier to predict visa approval likelihood, helping applicants optimize petitions. Benchmarked 5+ classification algorithms and achieved 74.4% accuracy by deploying CatBoost, addressing class imbalance through cost-sensitive loss weighting and optimal threshold tuning. Built production-ready inference service with real-time predictions, SHAP-based explainability, MLflow/DagsHub experiment tracking, and automated drift monitoring. Web Development Intern DRDO (June 2025 – August 2025) Developed CARS, a full-stack web application to digitize DRDO’s 10-stage contract acquisition workflow, replacing manual process tracking.

Built the Flask backend using Blueprints, form validation, and relational database models to manage multi- stage contract data.

Designed a wizard-style workflow with document and timeline tracking; owned backend development as 1 of 2 engineers.

SWATI SINGH

Computer Science undergraduate specializing in Machine Learning and AI engineering. Experienced in building and deploying end-to-end ML solutions and AI-powered applications, with a strong foundation in model development, evaluation and software engineering. EDUCATION

EXPERIENCE

Languages: Python, C++, JavaScript

AI/ML: PyTorch, Scikit-learn, Hugging Face

Development: FastAPI, Flask, React

MLOps & Tools: MLflow, Docker, Git, GitHub Actions Databases: MySQL, ChromaDB

Core CS: DSA, OOP, DBMS, Operating System

B.Tech in Computer Science & Engineering 2023-2027 Maharaja Agrasen Institute of Technology

CGPA: 9.08

PROJECTS

TECHNICAL SKILLS

CERTIFICATIONS & PUBLICATIONS

Research Mentor AI - Academic Research Assistant Github React, FastAPI, ChromaDB, Gemini, Supabase

Built AI-powered research assistant to help researchers discover relevant academic literature beyond keyword search using query intent understanding and semantic retrieval. Engineered semantic search across arXiv and Semantic Scholar using embeddings and reranking to surface relevant papers; implemented RAG system with ChromaDB and Gemini for question-answering over research PDFs and paper summarization.

Developed end-to-end React-FastAPI platform with PDF processing, retrieval APIs, Supabase persistence, and bookmarking, integrating AI workflows into a production-ready application. Machine Learning & AI Engineer

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