Applied Machine Learning Scientist with both hands-on and research experience on NLP and GenAI, with a publication at a top-tier machine learning conference (WWW), and specialized in developing tailored models for divers…
Applied Machine Learning Scientist with both hands-on and research experience on NLP and GenAI, with a publication at a top-tier machine learning conference (WWW), and specialized in developing tailored models for diverse NLP tasks to solve business problems.
<p>Developed a cutting-edge application for a recruiting agency to enhance job search efficiency by effectively matching job seekers’ resumes with available job positions, leading to an increased response rate from employers with LLM<br>
Scheduled an ETL pipeline powered by Apy to scrape and extract data from Linkedin, Indeed, etc., and further implemented data cleaning and designed databases to enhance overall efficiency<br>
Designed and architected a serverless computing solution on AWS utilizing Lambda and Chalice framework, further integrated Elasticsearch and Kibana for storing and visualizing the resume dataset<br>
Implemented a resume-job matching algorithm utilizing RAG models by GPT-3.5 and Llama using LangChain, resulting in a 20% increase in response rate, while leveraging VectorDB (FAISS) for vector embedding storage and context-specific retrieval<br>
Improved development processes by writing Pytest unit tests, connecting the CI/CD pipeline with GitHub Actions, actively monitoring model running status using AWS CloudWatch, and implementing an error-driven alarm system to ensure error detection and resolution</p>
• Developed a cutting-edge application for a recruiting agency to enhance job search efficiency by effectively matching job seekers’ resumes with available job positions, leading to an increased response rate from employers with LLM
• Scheduled an ETL pipeline powered by Apyfi to scrape and extract data from Linkedin, Indeed, etc., and further implemented data cleaning and designed databases to enhance overall efficiency • Designed and architected a serverless computing solution on AWS utilizing Lambda and Chalice framework, further integrated Elasticsearch and Kibana for storing and visualizing the resume dataset
• Implemented a resume-job matching algorithm utilizing RAG models by GPT-3.5 and Llama using LangChain, resulting in a 20% increase in response rate, while leveraging VectorDB (FAISS) for vector embedding storage and context-specific retrieval
• Improved development processes by writing Pytest unit tests, connecting the CI/CD pipeline with GitHub Actions, actively monitoring model running status using AWS CloudWatch, and implementing an error-driven alarm system to ensure error detection and resolution
<p>Designed and implemented a novel Transformer-based Topic-Aware Response Selection Model using PyTorch, enhancing coherence and consistency in personalized dialogue system responses<br>
Developed an innovative similarity-matching architecture incorporating word and topic-level semantics, resulting in a 1.21% on Recall@1 and 1.22% on MRR improvement by integrating a novel Topic-Aware Attentive Module<br>
Enhanced performance on Reddit empathetic datasets happy and offmychest with improvements of 1.10% and 1.15% respectively on Recall@1 metrics</p>
<p>Collaborated with the Customer Service team to develop bilingual conversational chatbots using cutting-edge language models in PyTorch on AWS EC2 within a Docker environment for development<br>
Enhanced model performance by preprocessing conversational dataset using NLTK and fine-tuning Huggingface's pre-trained Sentence-BERT models over 100k conversational datasets<br>
Improved intent detection accuracy for bilingual chatbots, leading to an accuracy improvement of 10% on English and 20% on French language models respectively</p>
<p>Led the migration of product databases from PostgreSQL (on AWS) to MySQL (on Alibaba Cloud), conducting research on available services and providing the executive team with detailed options and recommendations<br>
Designed database schema by analyzing the existing database, while following best practices for indexing and constraint for databases, and further developed Python and Bash scripts to facilitate migration</p>
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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