Highly motivated Computer Science Engineering (Honors) undergraduate specializing in AI/ML, with hands-on experience in LLM-powered NLP systems, backend development, and scalable ML pipelines. Proven ability to design an…
Highly motivated Computer Science Engineering (Honors) undergraduate specializing in AI/ML, with hands-on experience in LLM-powered NLP systems, backend development, and scalable ML pipelines. Proven ability to design and train custom transformer-based models, build end-to-end AI solutions, and optimize systems for real-world performance and accuracy. Experienced with PyTorch, FastAPI, distributed systems, and modern NLP techniques, including fine-tuning and RAG-based architectures. Passionate about solving complex problems, building production-ready AI systems, and pursuing a career as a Machine Learning Engineer or AI Software Engineer in impactful, technology-driven teams.
Independently led end-to-end development of a custom NLP summarizer model, Architected and trained custom transformer-based model using PyTorch, Engineered summarization algorithms optimizing compression ratio, Built evaluation metrics and loss functions, Developed context-aware fine-tuning pipeline, Created keyword extraction and entity recognition systems
Independently led end-to-end development of a custom NLP summarizer model from scratch for resume summarization, building proprietary algorithms.
Architected and trained custom transformer-based model using PyTorch, implementing attention mechanisms and specialized tokenization for resume-specific content, achieving 92% accuracy in key information extraction.
Engineered summarization algorithms optimizing the trade-off between compression ratio while maintaining 96% retention of critical skills, experiences, and qualifications.
Built evaluation metrics and loss functions specifically designed for improving summary quality scores by 40%.
Developed context-aware fine-tuning pipeline that adapts model outputs based on job descriptions and recruiter requirements, increasing recruiter satisfaction scores to 88%.
Created keyword extraction and entity recognition systems tailored for technical skills as per requirement.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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