Amirhossein Rahmani

Key Skills

Software

AWS SageMaker

Google Cloud Vertex AI

Top Subject Matter

Automated Vehicle Access (LPR system)

AI Chatbots – LLM Deployment & Tuning

Legal Services & Contract Review

Top Data Types

Image

Text

Video

Document

Top Task Types

Object Detection

Fine Tuning

Freelancer Overview

Autonomous License Plate Recognition (LPR) System - AI Model Training & Annotation. Brings 3 years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include PyTorch and AWS SageMaker. Education includes Bachelor of Science, University of Bojnord and High School Diploma, The National Organization for Development of Exceptional Talents (2019). AI-training focus includes data types such as Image and Text and labeling workflows including Object Detection and Fine-tuning.

Labeling Experience

AI Chatbot Development – LLM Evaluation & Fine-tuning

Aws SagemakerTextFine Tuning

I developed and deployed highly efficient AI chatbots by hosting pre-trained small Large Language Models (LLMs) and integrating them into client applications. The process involved fine-tuning LLMs and validating model outputs for client-specific use cases. I conducted model evaluation and iterative prompt engineering for continuous improvement. • Deployed and maintained custom AI chatbots on AWS EC2. • Conducted data quality reviews and model response evaluations. • Performed prompt and response validation for chatbot accuracy. • Integrated model feedback for iterative retraining and optimization.

I developed and deployed highly efficient AI chatbots by hosting pre-trained small Large Language Models (LLMs) and integrating them into client applications. The process involved fine-tuning LLMs and validating model outputs for client-specific use cases. I conducted model evaluation and iterative prompt engineering for continuous improvement. • Deployed and maintained custom AI chatbots on AWS EC2. • Conducted data quality reviews and model response evaluations. • Performed prompt and response validation for chatbot accuracy. • Integrated model feedback for iterative retraining and optimization.

2025

Autonomous License Plate Recognition (LPR) System - AI Model Training & Annotation

ImageObject Detection

I developed an autonomous License Plate Recognition (LPR) system using OpenCV and a custom-trained Convolutional Neural Network (CNN) with PyTorch. The system involved training models to detect and recognize vehicle license plates from real-time video streams. The solution was deployed on-premise, ensuring data privacy and sub-second recognition accuracy. • Built a data pipeline for ingesting and processing video streams using Python and OpenCV. • Annotated and labeled video frames manually for model training and evaluation. • Fine-tuned object detection models using PyTorch for high-accuracy plate recognition. • Automated cross-referencing of recognized plates with a local vehicle database for access control.

I developed an autonomous License Plate Recognition (LPR) system using OpenCV and a custom-trained Convolutional Neural Network (CNN) with PyTorch. The system involved training models to detect and recognize vehicle license plates from real-time video streams. The solution was deployed on-premise, ensuring data privacy and sub-second recognition accuracy. • Built a data pipeline for ingesting and processing video streams using Python and OpenCV. • Annotated and labeled video frames manually for model training and evaluation. • Fine-tuned object detection models using PyTorch for high-accuracy plate recognition. • Automated cross-referencing of recognized plates with a local vehicle database for access control.

2022 - 2024

Education

Work History