- Could you introduce yourself and tell us about you? Your current / recent jobs and employers? Previous companies and jobs?
He has over 8 years of IT experience, specializing in Machine Learning, Data Science, Deep Learning, and Large Language Models across industries such as F&B, Healthcare, and E-Commerce. He holds a Bachelor of Engineering in Computer Engineering and has completed additional certifications and practical training in ML. He began his career as a Data Scientist, building data pipelines and validation models that increased quotation acceptance and deal closures by 20%. He also developed an OCR-enabled web service for digitizing documents and a desktop application for image document segmentation with a user-friendly interface. Later moved to XXXX, as an ML Engineer, he designed and deployed machine learning solutions, including early LLM-based tools that helped reduce costs. He implemented AI tools to improve workflows, validated models using standard metrics, and applied software engineering practices like modular coding, version control, testing, and performance optimization. In his current role, at XXXX he works on models for behavior prediction, event detection, and spatiotemporal analysis of visual data. He has hands-on experience with Python, PyTorch, TensorFlow, and AWS SageMaker, integrating advanced algorithms to enhance reliability and scalability. He also mentors 3 junior developers, participates in code reviews, and leads the development of real-time computer vision and machine learning solutions for intelligent transportation and safety systems.
- What skill(s) / experience would you self-describe as strongest or specialist in?
His strongest skills are using modern technologies to build intelligent systems that can make a real impact. He has a solid background in artificial intelligence, machine learning, and data science, and specializes in creating reliable and scalable AI solutions. He has hands-on experience with cloud platforms like AWS and Azure, and has deployed AI models using container tools such as Docker. He is also skilled in Python, PyTorch, TensorFlow, and familiar with tools like Tableau and AWS for data analysis and visualization. For automation and development, he works with MLOps, Docker, Selenium, web scraping, and Databricks.
