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.
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