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AI Engineer with 1+ years in AI model development & deep learning
Results-oriented Junior AI/ML Developer with 1.5 years of hands-on experience in AI model development, deep learning, neural networks, and predictive modeling. Experienced in building high-accuracy models, including CNNs achieving 98% validation accuracy for healthcare diagnostics, transfer learning, NLP, anomaly detection, and model optimization. Skilled in API development and ML deployment. Immediately available for full-time AI/ML roles in the UAE.
SRM Institute of Science and Technology
Bachelor's Degree (B.Tech) · Computer Science and Engineering with Specialization in AI and ML
N/A – June 30, 2024
Nerve Digital Private Ltd
Junior Developer
July 1, 2024 – November 1, 2025
India
Intelligent Document QA System (RAG)
June 1, 2026 – Present
Developed a REST API using FastAPI for a conversational Retrieval-Augmented Generation (RAG) system that enables users to upload PDF documents and ask natural language questions with source-grounded responses. Built end-to-end RAG pipeline leveraging LangChain, including history-aware retriever, contextual query reformulation, and document chaining with Groq LLM (Llama-3.1). Implemented vector search using ChromaDB with Hugging Face sentence-transformer embeddings, along with intelligent PDF processing and session-based chat history management. Designed custom system prompts for strict grounding and deployed the application as a live REST API using ngrok with Swagger UI documentation.
E-commerce Sales Insights Dashboard using Power BI
June 1, 2026 – Present
Built an interactive Power BI dashboard using DAX and data visualisation techniques for e-commerce sales analysis by customer, category, state, and payment mode, incorporating KPI cards for Total Sales, Total Profit, Order Count, and Average Order Value, resulting in 20% faster business decision-making. Cleaned and transformed data using Power Query for the Power BI dashboard, created DAX measures for sales, profit, and quantity metrics, and built interactive bar, pie, donut, and trend charts with quarter slicers and filters to support faster, data-driven decision-making.
Data Center Technician
AWS Academy
June 1, 2026 – Present
Fundamentals of Deep Learning
NVIDIA Deep Learning Institute
June 1, 2026 – Present
Building Transformer-based Natural Language Processing Applications
NVIDIA Deep Learning Institute
June 1, 2026 – Present
Database Foundation
Oracle
June 1, 2026 – Present
SQL (Intermediate)
HackerRank
June 1, 2026 – Present
Power BI Workshop
Brain Tumor Detection using Convolutional Neural Networks (CNNs)
June 1, 2026 – Present
Performed data preprocessing and feature engineering on a 3,500-image brain MRI dataset including normalization and augmentation to improve model training. Applied Keras ImageDataGenerator for data augmentation with rescaling, rotation, and other transformations to reduce overfitting on limited medical images. Developed a high-performance CNN model using Conv2D layers, BatchNormalization, MaxPooling2D, Dropout, and Adam optimizer; achieved 98% validation accuracy, 97% precision, and 98% recall for brain tumor classification.
Be10x
June 1, 2026 – Present
ETL in Python & SQL
LinkedIn Learning
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from RAG systems and CNNs for medical imaging to Power BI dashboards, indicates a broad interest and adaptability, which can contribute positively to cultural fit. Their academic specialization in AI/ML and relevant certifications align well with an AI-focused role. The experience in a junior developer role, while short, shows exposure to real-world problem-solving and collaboration.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through their project work, such as optimizing SQL generation accuracy and reducing false positives in anomaly detection. Their ability to work on end-to-end pipelines (RAG, anomaly detection) suggests good operational fit and a structured approach to development. The descriptions indicate a results-oriented mindset with quantifiable achievements.