About Me

I am an AI Engineer with a strong focus on multi-model models, computer vision, robotics, and software development. I have hands-on experience with LLMs, VLLMs, ROS 2, Gazebo, and Nvidia Triton, and have deployed scalable solutions using AWS and Docker.

Previously, I worked as a Junior AI Engineer at NITEX, where I designed and deployed an automated fashion attributes tagging pipeline using multi-modal models. I also developed a service for extracting data from PDFs in JSON format, utilizing various APIs and cloud technologies to ensure efficiency and scalability.

My contributions to the Google Summer of Code’22 with TensorFlow involved implementing the Swin Video Transformer models and converting weights from PyTorch to TensorFlow. Additionally, as a Research Intern at DeepPavlov.ai, I created dialogue graphs from the MultiWOZ dataset using advanced machine learning techniques.

I am proficient in languages such as Python, C++, and CUDA, with expertise in frameworks like TensorFlow and PyTorch. In robotics, I am well-versed with ROS2, Gazebo, Nav2 and ros2_control. My experience extends to DevOps practices using Docker and Kubernetes, as well as backend development with FastAPI, PostgreSQL and ElasticSearch.

Beyond my technical skills, I am actively involved in leadership roles such as being a Qiskit Developer Advocate at IBM and a Microsoft Learn Student Ambassador. I am committed to continuous learning and sharing knowledge within the tech community.