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Machine Learning Engineer with 5+ years in AI innovation
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Competencies
Applied neural network architectures and deep learning techniques in AI model development.
Utilized NLP methods for language modeling, prompt engineering, and language understanding tasks.
Built scalable AI solutions using Docker, CI/CD pipelines, and cloud infrastructure for production deployment.
Performed data preprocessing, exploratory analysis, and visualization to interpret complex datasets.
Implemented knowledge graph integration and RAG techniques to improve AI reasoning capabilities.
Education
Languages
Summary
Experienced AI Engineer specialized in generative models, computer vision, NLP, and MLOps with a strong record of deploying scalable AI solutions.
Key Achievements
- Developed generative AI models and contributed to AI solution deployment and scalability.
- Led data preprocessing, exploratory data analysis, and feature engineering to enhance model accuracy.
- Contributed to academic research papers and formulated research hypotheses in AI.
Experience
Machine Learning Engineer
Developing cutting-edge solutions in Generative AI, Computer Vision, and Deep Learning, leveraging expertise in Neural Networks, image processing, and machine learning to drive AI innovation., Contributing to the development of GenAI models on custom data while ensuring seamless deployment and scalability., Proficient in Graph Knowledge & Retrieval-Augmented Generation (RAG) for enhanced AI reasoning, Agentic AI & Multi-Agent Systems for autonomous decision-making, Layout-based Segmentation & OCR, and LLM Fine-tuning for domain-specific applications., Hands-on experience in API creation, Dockerization, CI/CD pipelines, and scalable infrastructure for deploying production-ready AI solutions.
Artificial Intelligence Training
Engaged as an AI Trainee focused on algorithm development in Machine and Deep Learning platform., Led data preprocessing, exploratory data analysis, and feature engineering to boost model accuracy and performance., Explored NLP and Computer vision core topics and contributed to projects by applying advanced analytical techniques and statistical models, extracting actionable insights from complex datasets to drive impactful results.
Artificial Intelligence Intern (Remote)
Focused on cutting-edge technologies in Machine Learning, Deep Learning, Time Series Analysis, and NLP., The internship involved specialized coursework that significantly enhanced technical proficiency and deepened expertise in advanced AI methodologies.
Research Assistant (Remote)
Collaborated with a Ph.D. student from The University of Texas at El Paso on academic research and assignments, contributing to the development of some research papers as well as the formulation of research hypotheses and methodologies.