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.
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 Apy 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
• 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
Designed and implemented a novel Transformer-based Topic-Aware Response Selection Model using PyTorch, enhancing coherence and consistency in personalized dialogue system responses
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
Enhanced performance on Reddit empathetic datasets happy and offmychest with improvements of 1.10% and 1.15% respectively on Recall@1 metrics
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
Enhanced model performance by preprocessing conversational dataset using NLTK and fine-tuning Huggingface's pre-trained Sentence-BERT models over 100k conversational datasets
Improved intent detection accuracy for bilingual chatbots, leading to an accuracy improvement of 10% on English and 20% on French language models respectively
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
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
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