Manvi Malik

Management Lead / Coordinator

IndiaSoftware Engineering and Data Science
2roles
25skills
3education
1credentials

About

B.Tech AIML student with an 8.0 SGPA, IBM-certified AI/ML training, and hands-on experience developing machine learning and LLM-based projects.

Experience

Technical Intern (Certified)

IBM

July 2025 – August 2025 · Remote

Underwent intensive training in Artificial Intelligence and Machine Learning; applied theoretical concepts to real-world datasets; collaborated with industry mentors to understand enterprise-level SDLC.

Management Lead / Coordinator

TEDxAKGEC

2023 – Present · Ghaziabad, UP

Orchestrated logistics and operational workflows for campus events with 500+ attendees; managed stakeholder communications and event timelines; improved team productivity through structured task tracking for management volunteers.

Education

Ajay Kumar Garg Engineering College (AKGEC)

B.Tech, Artificial Intelligence and Machine Learning

2023 – 2027

Current SGPA: 8.0

Scottish International School

Class XII (Senior Secondary), CBSE Board

2022

88%

Scottish International School

Class X (Secondary), CBSE Board

2020

95%

Skills

PythonC/C++SQLHTML/CSSJavaScriptRegression AnalysisRandom ForestGradient BoostingScikit-learnPandasNumPyGitGitHubVS CodeGoogle Cloud PlatformMS OfficeMachine LearningArtificial IntelligenceLLMsRetrieval-Augmented GenerationVector DatabasesLLM EvaluationPromptingEmbeddingsSimilarity Search

Projects

Salary Prediction using Regression

Developed a salary prediction model using Python, Scikit-learn, Pandas, and GitHub. Cleaned and preprocessed data using label encoding and duplicate removal; compared Linear Regression, Random Forest, and Gradient Boosting; and implemented a Voting Regressor ensemble.

NyayaGPT – RAG-Based Legal AI Assistant

Developed a Retrieval-Augmented Generation system mapping natural-language crime descriptions to relevant BNS/BNSS Acts. Used embeddings and similarity search across 1,500+ indexed law sections, improving retrieval accuracy to approximately 85% and reducing response latency from approximately 3.8 seconds to 2.1 seconds.

Email Reply Suggester

Built an LLM-powered email reply system using few-shot prompting, Llama 3.3 70B, and Groq. Developed an evaluation pipeline measuring correctness, factuality, tone, and conciseness, with hold-out evaluation and human-versus-LLM scorer validation.