Sina Ho jjati

AI Software Engineer at WAT.ai

Designed and implemented an end-to-end solution to produce high-quality AI-generated advertisement videos affordably, eliminating the reliance on costly production methods. Automated the generation of marketing content by leveraging LLMs, enabling users to produce high-quality, customized materials with minimal effort. Built a user-friendly interface for video sharing across social media platforms, enhancing content distribution efficiency and increasing user engagement by 25%.

Machine Learning Engineer at Synervoz

Designed and deployed RAG-based real-time audio AI agents, optimizing system performance and reducing latency by 45%. Engineered and implemented robust data pipelines for testing, validating, and deploying audio processing workflows, supporting 10k+ parallel audio streams. Architected and fine-tuned speech-to-text generation model powering real-time audio chatbots, achieving over 90% ASR accuracy.

AI Software Engineer at WAT.ai

Designed and implemented an end-to-end solution to produce high-quality AI-generated advertisement videos affordably, eliminating reliance on costly production methods. Automated the generation of marketing content by leveraging LLMs, enabling users to produce high-quality, customized materials with minimal effort. Built a user-friendly interface for video sharing across social media platforms, enhancing content distribution efficiency and increasing user engagement by 25%.

Machine Learning Engineer at Synervoz

Designed and deployed RAG-based real-time audio AI agents, optimizing system performance and reducing latency by 45%. Engineered robust data pipelines for testing, validating, and deploying audio processing workflows, supporting 10k+ parallel audio streams. Architected and fine-tuned speech-to-text generation model powering real-time audio chatbots, achieving over 90% ASR accuracy.

AI Software Engineer at WAT.ai

Designed and implemented an end-to-end solution to produce high-quality AI-generated advertisement videos affordably, eliminating the reliance on costly production methods. Automated the generation of marketing content by leveraging LLMs, enabling users to produce high-quality, customized materials with minimal effort. Built a user-friendly interface for video sharing across social media platforms, enhancing content distribution efficiency and increasing user engagement by 25%.

Machine Learning Engineer at Synervoz

Designed and deployed RAG-based real-time audio AI agents, optimizing system performance and reducing latency by 45%. Engineered and implemented robust data pipelines for testing, validating, and deploying audio processing workflows, supporting 10k+ parallel audio streams. Architected and fine-tuned speech-to-text generation model powering real-time audio chatbots, achieving over 90% ASR accuracy.

Machine Learning Engineer at University of Waterloo

Developed an advanced text-to-image generation model, employing CNNs and LLMs to transform textual descriptions into high-fidelity images. Engineered a chatbot system using Hugging Face Transformers for precise intent recognition and image processing. Designed models to generate descriptive texts from images and videos, leveraging CNNs for feature extraction and transformer models for text generation.

Machine Learning Engineer at University of Waterloo

Developed advanced text-to-image generation model, employing CNNs and LLMs to transform textual descriptions into high-fidelity images. Engineered a chatbot system using Hugging Face Transformers for precise intent recognition and image processing, and designed a model to generate descriptive texts from images and videos.

Machine Learning Engineer at University of Waterloo

Developed advanced text-to-image generation model, employing CNNs and LLMs to transform textual descriptions into high-fidelity images. Engineered a chatbot system using Hugging Face Transformers for precise intent recognition and image processing algorithms to facilitate image modifications based on text prompts. Designed a model to generate descriptive texts from images and videos, utilizing CNNs for feature extraction and transformer models for precise text generation.

Machine Learning Engineer at DigiKala

Developed an AI-powered chatbot using LLMs and Retrieval-Augmented Generation (RAG) for an eCommerce platform to automatically answer customer queries, enhancing satisfaction and supporting scalable support. Developed models to predict sales patterns for 6k+ products based on behavioral data, driving targeted marketing. Designed a real-time recommendation engine using collaborative filtering with Pandas, Scikit-Learn, and TensorFlow, improving retention by 38% and click-through rates by 20% through personalization.

Machine Learning Engineer at DigiKala

Developed an AI-powered chatbot using LLMs and RAG for eCommerce to automatically answer customer queries about products; developed a model to predict sales patterns for 6k+ products based on behavioral data, leading to a 30% increase in targeted marketing effectiveness. Designed a real-time recommendation engine using collaborative filtering with Pandas, Scikit-Learn, and TensorFlow that improved customer retention by 38% and increased click-through rates by 20%.

Machine Learning Engineer at DigiKala

Developed an AI-powered chatbot using LLMs and RAG for eCommerce platform to automatically answer customer queries about products, enhancing customer satisfaction and streamlining support processes. Developed and trained a model to predict the pattern of sales for 6k+ products based on behavioral data leading to a 30% increase in targeted marketing effectiveness. Designed a real-time recommendation engine using collaborative filtering methods with Pandas, Scikit Learn, and TensorFlow that improved customer retention by 38% and increased click-through rates by 20% via personalized recommendations.

Data Scientist at Cafe Bazaar

Implemented and maintained a real-time machine learning pipeline for fast decision-making, reducing response times by 20%. Built NLP pipelines to analyze customer feedback and identify product improvement areas, contributing to a 25% increase in customer satisfaction. Enhanced recommendation system accuracy by processing extensive customer reviews.

Data Scientist at Cafe Bazaar

Implemented and maintained a machine learning pipeline for real-time data processing, enabling faster decision-making and reducing response time by 20%. Designed and developed a machine-learning model to analyze customer feedback data, leading to product improvements and a 25% increase in customer satisfaction scores. Developed and maintained NLP pipelines for processing extensive customer reviews, contributing to a 15% enhancement in the accuracy of the recommendation system.