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AI Engineer with less than a year in Data Science & Machine Learning.
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 Engineer with a strong foundation in Deep Learning, NLP, and LLM development, complemented by hands-on experience in building and deploying AI-powered applications. Proficient in Python, cloud platforms like Azure, and frameworks such as FastAPI and PyTorch. Currently contributing to user interaction data storage systems and passionate about developing innovative solutions for intelligent document analysis and medical question-answering.
Datta Meghe College of Engineering, Airoli
B.E. · Artificial Intelligence & Data Science Engineering
August 1, 2022 – June 30, 2026
Syra
January 1, 2026 – Present
Developed a lightweight, developer-focused AI chatbot web application using Streamlit and Groq API to integrate the LLaMA 3 (70B) language model. Deployed on the application on Azure Web Apps.
Gemma Fine-Tuning
October 1, 2025 – Present
Fine-tuned Google's Gemma 2B LLM on the ChatDoctor HealthCareMagic 100k dataset to specialize in medical question answering.
View ProjectCurioBot
September 1, 2025 – Present
Developed a FastAPI-based web application integrating LLMs (via Groq), LangChain, and FAISS for intelligent document analysis. Integrated Azure services (Azure Blob, Azure Open-AI) and FAISS Vector db.
Transformer From Scratch
July 1, 2025 – Present
Implemented a full-stack Transformer architecture from scratch using the PyTorch Tensor, including custom Multi-Head Attention, Positional Encoding, and Masking.
View ProjectCertification in Deep Learning
DeepLearning.ai
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in cutting-edge AI technologies and practical application, which aligns well with an innovative and fast-paced AI engineering culture. The diversity of projects, from foundational model implementation to full-stack application development and fine-tuning, suggests adaptability and a broad technical curiosity. The academic background and certifications further support a learning-oriented mindset. However, the lack of team-based project descriptions (beyond the co-curricular 'Tech Lead' role) limits the assessment of collaborative cultural fit.
Soft Skills & Operational Fit
The candidate's resume indicates a proactive approach to learning and project development, suggesting good self-motivation and initiative. Experience as a 'Tech Lead' in a co-curricular activity points to potential leadership and teamwork skills. However, without specific behavioral assessment data or interview transcripts, a comprehensive evaluation of soft skills and operational fit is limited.