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AI Engineer with less than a year in Multimodal AI Systems, LLM Pipelines & Computer Vision
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AI & ML Engineering Graduate with hands-on experience building multimodal AI systems, LLM-integrated pipelines, and CNN-based computer vision applications. Proven ability to design end-to-end AI infrastructure combining cloud-based LLMs (GPT-40) and local models with NLP capabilities including semantic understanding, text classification, and conversational AI. Experienced in prompt engineering, LangChain orchestration, Flask REST API development, and scalable Python application design. Passionate about building modular, extensible Al systems that bridge language and vision intelligence.
Savitribai Phule Pune University
B.E. · Artificial Intelligence and Machine Learning
August 1, 2021 – June 30, 2025
R.P. College
HSC (12th Grade)
June 1, 2021 – May 31, 2021
Aryachankya High School
SSC (10th Grade)
June 1, 2019 – May 31, 2019
SkillEcted Pvt. Ltd.
Data Analyst Intern.
March 1, 2025 – June 1, 2025
Pune, Maharashtra, India
TeachNook Pvt. Ltd.
Machine Learning Intern (Remote).
September 1, 2023 – November 1, 2023
India
Multi-LLM Router & Gateway
June 1, 2026 – Present
Built a unified LLM gateway that routes user prompts dynamically across multiple cloud-based (GPT-40) and local models (LLaMA 3, DeepSeek via Ollama) through a single Flask REST API endpoint. Implemented intelligent prompt routing logic with fallback strategies - automatically switching to a backup model when primary model fails - and monitored token usage per request for cost optimization.
View ProjectBrain Tumor Detection using CNN & VGG16 Transfer L.
June 1, 2026 – Present
Built a medical image classification system using CNN to detect brain tumors from MRI scans. Applied VGG16 transfer learning for deep learning for deep feature extraction, improving model accuracy and generalization. Performed image preprocessing, normalization, and augmentation using OpenCV & NumPy to enhance model accuracy.
View ProjectReal-Time Object Detection with LLM Scene Understanding.
June 1, 2026 – Present
Built a multimodal AI system combining YOLOv8 object detection with LLM-based natural language scene understanding - detected objects are passed as structured prompts to GPT-40 to generate human-readable scene descriptions in real time. Implemented semantic search over stored scene embeddings using ChromaDB, enabling natural language queries like "find all scenes with people near vehicles" across processed image history. Designed a modular vision-language pipeline with OpenCV-based frame preprocessing, bounding box extraction, dynamic prompt construction, and Streamlit-based interactive interface for live or uploaded media input.
View ProjectPython
Hackerrank
June 1, 2026 – Present
SQL
Hackerrank
June 1, 2026 – Present
Machine Learning Course & Internship
TeachNook
June 1, 2026 – Present
GenAI Powered Data Analytics
Forage (TATA)
June 1, 2026 – Present
Data Analyst Course & Internship
SkillEcted Pvt. Ltd.
June 1, 2026 – Present
Docker from Zero
MindLuster
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in cutting-edge AI technologies, aligning well with an innovative and research-oriented culture. The focus on building practical, real-world applications (e.g., brain tumor detection, real-time object detection) suggests a results-driven mindset. The personal projects indicate self-motivation and a passion for AI beyond academic requirements. However, the lack of team-based project experience or explicit collaboration details limits the assessment of cultural fit in a team environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and problem-solving approach, particularly in designing modular systems and implementing fallback strategies. The diversity of projects suggests adaptability and a willingness to tackle complex challenges. However, without direct assessment data on communication or teamwork, further evaluation of soft skills is limited.