AI Engineer with less than a year in RAG pipelines and deep learning models
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI/ML engineer with hands-on experience building end-to-end RAG pipelines, LLM-based conversational systems, and deep learning models. Proficient in LangChain, FastAPI, and vector databases. Passionate about building production-ready AI applications and actively seeking AI/ML or Data Science internship opportunities.
Savitribai Phule Pune University
B.Tech · Computer Engineering
August 1, 2024 – June 30, 2027
MSBTE
Diploma · Computer Engineering
August 1, 2021 – June 30, 2024
Vesatogo Innovations Pvt. Ltd.
Flutter Developer Intern
July 1, 2024 – January 1, 2025
Nashik, Maharashtra, India
BreedLens - Dog Breed Classifier using Transfer Learning
June 24, 2026 – Present
Fine-tuned EfficientNet-B3 on the Stanford Dogs Dataset (120 breeds, 20,580 images) using transfer learning with custom classification head. Achieved top-3 predictions with confidence scores, supporting both image URL and direct file uploads via a REST API. Optimized model for CPU inference and deployed via Flask REST API, reducing average inference time for production-like usage.
View ProjectRepoMind - AI Code Assistant for GitHub Repositories
June 24, 2026 – Present
Built an end-to-end RAG pipeline for GitHub repositories using language-aware boundary chunking to preserve code context across file types. Implemented dual-mode semantic search (dense + keyword) using Sentence-Transformers and ChromaDB, improving retrieval relevance for code queries. Integrated Ollama (Qwen2.5-Coder) with multi-turn chat history and context-aware prompt engineering for accurate, codebase-grounded responses. Developed an async FastAPI backend with efficient ingestion queues, enabling concurrent repository indexing without blocking query endpoints.
View ProjectCultural Fit Analysis
The candidate's projects demonstrate initiative and a passion for AI/ML, which aligns well with an innovative and growth-oriented culture. The diversity of projects (NLP/RAG for code, computer vision for image classification) shows a broad interest in AI applications. The candidate is actively seeking an AI/ML or Data Science internship, indicating a strong desire to learn and contribute, which is a positive cultural fit for entry-level or junior roles. The Flutter internship also shows versatility.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to work on complex technical challenges. The detailed explanations of architectural choices (e.g., language-aware chunking, dual-mode semantic search, async backend) suggest good analytical and design thinking. However, without direct interaction or psychometric test results, specific soft skills like teamwork, leadership, or adaptability cannot be fully assessed.