Available to hire
Hi, I’m Lee Anwar, a seasoned Machine Learning Engineer with over a decade of experience specializing in Generative AI and large language models. I love building robust machine learning pipelines that connect innovative research with practical, real-world applications. I take pride in optimizing models, designing scalable cloud deployments, and collaborating across teams to deliver AI solutions that truly impact business outcomes.
I’m passionate about advancing AI technology while ensuring that the solutions I build are efficient, scalable, and usable in production environments. Outside of work, I also enjoy sharing knowledge and mentoring others on best practices in the AI and ML space.
Skills
Language
English
Fluent
Work Experience
Senior Machine Learning Engineer at Amazon
January 1, 2020 - PresentOwned end-to-end development of AI agents using LangChain and React prompting to automate complex workflows, aligning with customer-focused solutions and innovative simplification. Scaled RAG-based knowledge systems using AWS OpenSearch and vector databases (FAISS, Pinecone) to improve LLM accuracy for enterprise applications, similar to Amazon Kendra and Alexa. Drove model excellence by implementing evaluation frameworks (BLEU, ROUGE, hallucination detection) to ensure reliable, production-ready AI systems. Delivered optimized LLMs by fine-tuning open-source models (LLaMA, GPT-J) on proprietary datasets, focusing on deep customer needs. Deployed serverless AI solutions on AWS (Lambda, ECS, SageMaker) with CI/CD pipelines for seamless, zero-downtime updates. Accelerated team productivity by developing prompt engineering tools and dataset versioning systems to streamline experimentation. Communicated technical strategy to leadership and partners through whitepapers and architecture revi
Machine Learning Engineer at Haithem Tech
December 31, 2019 - July 25, 2025Designed and trained custom LLMs using Hugging Face, BERT, RoBERTa, and GPT-2 for specialized applications including legal document processing, customer service automation, and technical content generation. Developed and deployed enterprise-grade NLP systems for intelligent search, document summarization, and conversational AI, enhancing operational efficiency and user experience. Managed the complete machine learning pipeline from data collection and cleaning to model training, optimization, deployment, and ongoing performance monitoring in production environments. Created comprehensive evaluation frameworks to analyze model outputs for ethical considerations, including bias detection, toxicity scoring, and factual accuracy verification. Established MLOps workflows incorporating model versioning, automated retraining pipelines, and A/B testing to ensure consistent model performance and reliability. Conducted technical training sessions on advanced NLP concepts and mentored engineering
Junior Machine Learning | NLP Engineer at Insight AI Corp
January 31, 2018 - July 25, 2025Developed and deployed NLP solutions for named entity recognition, topic modeling, and sentiment analysis to extract insights from unstructured text data. Built efficient natural language processing pipelines using spaCy, NLTK, and Gensim for text preprocessing, feature extraction, and document analysis. Designed and implemented RESTful APIs using FastAPI and Flask to serve NLP models in production environments with low-latency requirements. Worked closely with data analysts and domain experts to identify key features, validate model outputs, and ensure business relevance of NLP applications. Optimized text processing workflows with custom tokenization, lemmatization, and domain-specific vocabulary enhancements to improve model performance. Established monitoring systems to track model predictions, detect anomalies, and maintain quality of NLP services in production.
Senior Machine Learning Engineer at Amazon
January 1, 2020 - PresentOwned end-to-end development of AI agents using LangChain and React prompting to automate complex workflows, aligning with customer-focused solutions and innovative simplification. Scaled RAG-based knowledge systems using AWS OpenSearch and vector databases to improve LLM accuracy for enterprise applications, similar to Amazon Kendra and Alexa. Implemented evaluation frameworks to ensure production-ready AI systems. Delivered optimized LLMs by fine-tuning open-source models on proprietary datasets. Deployed serverless AI solutions on AWS with CI/CD pipelines for seamless updates. Developed prompt engineering tools and dataset versioning systems to streamline experimentation. Communicated technical strategy through whitepapers and architecture reviews to promote scalable AI adoption.
Machine Learning Engineer at Haithem Tech
December 31, 2019 - July 25, 2025Designed and trained custom large language models using Hugging Face, BERT, RoBERTa, and GPT-2 for specialized applications including legal document processing, customer service automation, and technical content generation. Developed and deployed enterprise-grade NLP systems for intelligent search, document summarization, and conversational AI, enhancing operational efficiency and user experience. Managed the complete ML pipeline from data collection to deployment and performance monitoring. Created evaluation frameworks for ethical considerations including bias detection and factual accuracy verification. Established MLOps workflows with model versioning, automated retraining, and A/B testing. Conducted technical training sessions on NLP and mentored engineering teams.
Junior Machine Learning | NLP Engineer at Insight AI Corp
January 31, 2018 - July 25, 2025Developed and deployed NLP solutions for named entity recognition, topic modeling, and sentiment analysis to extract insights from unstructured text data. Built efficient NLP pipelines using spaCy, NLTK, and Gensim for text preprocessing and feature extraction. Designed and implemented RESTful APIs using FastAPI and Flask to serve NLP models in production with low latency. Collaborated with data analysts and domain experts to validate model outputs ensuring business relevance. Optimized text processing workflows with custom tokenization and domain-specific vocabulary. Established monitoring systems to track predictions and maintain NLP service quality.
Education
Bachelor's at National University of Science and Technology
January 1, 2013 - December 31, 2013Bachelor's at National University of Science and Technology
January 1, 2009 - December 31, 2013Qualifications
Industry Experience
Software & Internet, Telecommunications, Professional Services, Computers & Electronics, Education, Financial Services, Energy & Utilities
Skills
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