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Schedule Interview NowAt Softaims, I have been fortunate to work in an environment that values creativity, precision, and long-term thinking. Each project presents a unique opportunity to transform abstract ideas into meaningful digital experiences that create real impact. I approach every challenge with curiosity and commitment, ensuring that every solution I design aligns not just with technical requirements, but also with human needs and business objectives. One of the most rewarding aspects of my journey here has been learning how to bridge the gap between innovation and practicality. I believe technology should simplify complexity, enhance efficiency, and empower people to do more with less friction. Whether building internal systems, optimizing workflows, or helping bring client visions to life, my focus remains on developing solutions that stand the test of time. Softaims has encouraged me to grow beyond coding—to think about design, communication, and sustainability in technology. I see every project as part of a larger ecosystem, where small details contribute to long-lasting results. My daily motivation comes from collaborating with people who share the same passion for doing meaningful work, and from seeing the tangible difference our efforts make for clients around the world. More than anything, I value the culture of learning and improvement that defines Softaims. It’s a place where ideas evolve through teamwork and constructive feedback. My goal is to continue refining my craft, exploring new approaches, and contributing to solutions that are not only efficient but also elegant in their simplicity.
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Potentially possible
This project developed a Vision Transformer model to classify satellite images for Amazon deforestation monitoring. We achieved strong performance, as evidenced by the F-beta scores (around 0.85) and decreasing loss.
AI-powered banking chatbot, featuring domain-adapted finetuning for specialized expertise, Retrieval-Augmented Generation (RAG) for accurate answers, and robust guardrails for secure, safe interactions.
This project demonstrates object detection on car images using the YOLO (You Only Look Once) model. It involves data preprocessing, model training, and object detection with YOLO.
Social Media Content Generation Automation
Deep learning model using MobileNet to classify 38 plant diseases with 96%+ accuracy. Ideal for smart agriculture apps.
Bachelor of Engineering (BEng) in Software Engineering