As a Senior Solution Architect, I specialize in Deep Learning Deployment and Optimization, with a focus on Edge Computing using NVIDIA frameworks such as TensorRT, TAO, Omniverse, Metropolis, AMMO, Triton, and DeepStream. My role spans the entire computer vision pipeline architecture, from data collection to model deployment.A significant part of my work involves deploying Large Language Models (LLMs) and Generative AI models, including vision transformers and multimodal models, on edge devices like NVIDIA Jetson. In addition to generating proof-of-concepts (POCs) and providing consultation to startups in the NVIDIA Inception Program, I am also a Certified Deep Learning Instructor at the NVIDIA Deep Learning Institute (DLI). I also have the opportunity to present at NVIDIA gatherings, where I share insights and advancements in the field of deep learning and edge computing.

Directing a team in the development of computer vision algorithms, and spearheading the design of intricate algorithmic solutions employing neural networks for complex scenarios.

As a Software Engineer specializing in Deep Learning and Computer Vision, my responsibilities encompassed developing and optimizing neural network inference frameworks using Python, C++, and NVIDIA DeepStream. I was integral in managing and developing our main data pipeline, and I actively engaged in training Machine Learning models, alongside performing other MLOps tasks. Moreover, I efficiently carried out project management duties, ensuring successful planning and execution of our product development.

As a Software Engineer at Siemens DISW, I was a key member of the Core Robotics Team, specializing in the physical simulation of robotic operations. My role involved developing and implementing algorithms for simulating complex robotic movements and interactions, contributing to the advancement of robotic technologies within the organization.In addition to this, I was also part of a development team focused on creating synthetic computer vision data for automatic robotic path planning. This involved generating high-quality synthetic data, training machine learning models, and developing algorithms for efficient and accurate path planning.

Student role - Tasked with the creation of instructional materials focused on robotic simulation within the Tecnomatix digital twin environment. Additionally, I developed Python scripts to automate various processes. I also contributed to the development of a computer vision system for robotic operations.

Head of the sa'ar 6 learning and operating project in the Navy Command.

Rank: Lieutenant Commander (OF-3, Rav-Seren)

As the Chief Engineer on a Saar 5 Missile Ship, I led the technical department and commanded a team of over 30 personnel. My responsibilities encompassed the management and maintenance of complex onboard systems, ensuring operational readiness. I actively participated in numerous operational activities, demonstrating quick decision-making and resilience in the demanding environment of the Israeli Navy.