AI Engineer

Experienced Deep Learning Architect and Researcher with a background in Quantitative Development for various financial desks. Skilled in Computer Vision, Neural Networks, and Generative Models. Proficient in a wide range of frameworks and techniques including Transformers, GANs, and Probabilistic Time Series Models. Extensive knowledge in Optimization Algorithms, Deep Reinforcement Learning, and Machine Learning methods such as SVM and Clustering. Passionate about exploring new technologies and pushing the boundaries of AI and finance.

Translation: I developed quantitative models and tools for various trading desks and risk management platforms, with a focus on equity derivatives, index products, and single stock desks. I also worked on statistical arbitrage strategies and risk management for prime brokerage clients.

I was responsible for creating quantitative models and algorithms for portfolio management and market risk analytics. This role involved developing tools and strategies to assess and optimize portfolio performance.

I specialized in designing deep learning architectures and conducting research, particularly in the field of computer vision models such as ResNet, ConvNetXt, and MobileNet. My work also involved transfer learning, fine-tuning, and implementing object detection algorithms like YOLOv2 and SSD.