- Head of the Machine Learning team- Leading a team of scientists and developers to deliver innovative, distributed, fault-tolerant AI solutions, while having over 99% uptime, improving system accuracy by 76% and speed by 4x via robust microservice system design and implementation, custom Deep Learning network design, and specialized code development- Head of the Software Architecture team- Designed, architectured, and led the development of distributed, fault-tolerant, and resilient cloud-native systems of microservices from scratch in Rust, Python, and C++, supporting high-throughput, real-time data processing- Architecting real-time data pipelines enabling instant analytics and decision making- Providing full-stack DevOps automation including CI/CD, Kubernetes, monitoring, networking, infrastructure automation, along with Linux system administrations and security- Managing team for R&D of multi-modal AI for weed detection, combining computer vision, NLP, and sensor data inputs- Leading Deep Learning research team in designing innovative solutions, architecting custom neural networks, and advancing state-of-the-art techniques to enhance product capabilities - Delivering stable and robust Deep Learning based product in a resilient software application- Optimized machine learning pipelines, improving throughput and reliability to over 99% uptime through robust architecture, system design, and proactive monitoring- Developed cutting-edge distributed deep learning framework in Python, Rust, Cuda, and C++, enabling unified training of diverse DL architectures with distributed training, accelerated debugging, logging, and metrics, surpassing the speed and capabilities of existing solutions like PyTorch Lightning- Pioneered R&D initiatives fusing AI and robotics- Deploying Deep Learning solutions to embedded devices and tailoring them for highly efficient performance- Developing software in Rust, C++, Python, Go, and Scala

Holding the lead on a Machine Learning project for Natural Language Processing and Understanding.Developing Natural Language Understanding models for Ford Motor Company.

Scientist in Research and Development section.Proposed, implemented, and applied innovative state-of-the-art Machine Learning and Deep Learning techniques on auto insurance carriers to detect and evaluate damages in a car crash based on the user-uploaded data of the accident including photos. Increased the efficiency of applications of Deep Learning techniques by robust code development in multiple programming languages, code optimization, and development and implementation of parallel processing on NVIDIA CUDA.

Held labs for and taught Electronics I and II.

Conducted research on and published in the fields of Mathematical Optimization, Machine Learning and Artificial Intelligence, and waveform design for active sensing. Designed and developed several Optimization frameworks for Machine Learning and Radar applications with MATLAB, C/C++, Python, JAVA, and Scala.Manuscript reviewer for IEEE Transactions on Signal Processing and ELSEVIER.Research interests include Machine Learning, Artificial Intelligence, Optimization, Software Engineering, and Robotics.

Conducted research on Pilot Signal Design for Channel Estimation.

- Electronics I, II, and III- Communication Circuits- Antenna Engineering

Optimized and maintained local cellular networks.Developed maintenance programs in C/C++.

Taught English at advanced level.

Graphic Designer, Typographer, and Layout Designer at Shahrat Journal, the nation-wide Journal of Art and Urban Planning.Won the best nation-wide Layout and Graphic Designer award.

Taught Math and Physics at Allame Helli, the school for the talented, at pre-university grade.

Lead the national committee to coordinate visits of numerous incoming trainees. Negotiated with multitudinous employers and government officials to create job position and facilitate the move of incoming trainees.