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Hi, I'm Arbaaz Dharmavaram, a passionate Full Stack and AI/ML Engineer with over five years of experience developing machine learning and backend systems. I've had the opportunity to work with renowned institutions like the University of New Brunswick and Target, and I hold two U.S. patents along with multiple research publications. I'm very comfortable working with technologies including PyTorch, TensorFlow, and Kubernetes, and I love creating innovative solutions that solve real-world problems. Throughout my career, I've led significant projects such as AI-driven vulnerability management and automated self-checkout security systems, blending AI with software engineering to deliver impactful products. I enjoy staying at the forefront of AI research and development and continuously learning to enhance my skill set and contribute meaningfully to my field.…Hi, I'm Arbaaz Dharmavaram, a passionate Full Stack and AI/ML Engineer with over five years of experience developing machine learning and backend systems. I've had the opportunity to work with renowned institutions like the University of New Brunswick and Target, and I hold two U.S. patents along with multiple research publications. I'm very comfortable working with technologies including PyTorch, TensorFlow, and Kubernetes, and I love creating innovative solutions that solve real-world problems. Throughout my career, I've led significant projects such as AI-driven vulnerability management and automated self-checkout security systems, blending AI with software engineering to deliver impactful products. I enjoy staying at the forefront of AI research and development and continuously learning to enhance my skill set and contribute meaningfully to my field.

Arbaaz Dharmavaram

Full Stack Developer, AI Engineer, Data Scientist, +1

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Hi, I'm Arbaaz Dharmavaram, a passionate Full Stack and AI/ML Engineer with over five years of experience developing machine learning and backend systems. I've had the opportunity to work with renowned institutions like the University of New Brunswick and Target, and I hold two U.S. patents along with multiple research publications. I'm very comfortable working with technologies including PyTorch, TensorFlow, and Kubernetes, and I love creating innovative solutions that solve real-world problems. Throughout my career, I've led significant projects such as AI-driven vulnerability management and automated self-checkout security systems, blending AI with software engineering to deliver impactful products. I enjoy staying at the forefront of AI research and development and continuously learning to enhance my skill set and contribute meaningfully to my field.…Hi, I'm Arbaaz Dharmavaram, a passionate Full Stack and AI/ML Engineer with over five years of experience developing machine learning and backend systems. I've had the opportunity to work with renowned institutions like the University of New Brunswick and Target, and I hold two U.S. patents along with multiple research publications. I'm very comfortable working with technologies including PyTorch, TensorFlow, and Kubernetes, and I love creating innovative solutions that solve real-world problems. Throughout my career, I've led significant projects such as AI-driven vulnerability management and automated self-checkout security systems, blending AI with software engineering to deliver impactful products. I enjoy staying at the forefront of AI research and development and continuously learning to enhance my skill set and contribute meaningfully to my field.

Available to hire

Hi, I’m Arbaaz Dharmavaram, a passionate Full Stack and AI/ML Engineer with over five years of experience developing machine learning and backend systems. I’ve had the opportunity to work with renowned institutions like the University of New Brunswick and Target, and I hold two U.S. patents along with multiple research publications. I’m very comfortable working with technologies including PyTorch, TensorFlow, and Kubernetes, and I love creating innovative solutions that solve real-world problems.

Throughout my career, I’ve led significant projects such as AI-driven vulnerability management and automated self-checkout security systems, blending AI with software engineering to deliver impactful products. I enjoy staying at the forefront of AI research and development and continuously learning to enhance my skill set and contribute meaningfully to my field.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Advanced

Work Experience

Software Engineer at Canadian Institute for Cybersecurity (University of New Brunswick)

December 1, 2023 - Present

Led AI-driven Vulnerability Management by automating the prioritization of risk mitigation. Integrated multiple data sources including the National Vulnerability Database, CVE.org, SHODAN, Exploit-DB, and web threat intelligence. Developed a threat intelligence pipeline leveraging Agentic AI and Retrieval-Augmented Generation (RAG) to extract actionable insights, managed in PostgreSQL, and visualized through PowerBI dashboards.

Senior Engineer, Computer Vision and AI at Target Corporation

July 1, 2023 - August 23, 2025

Developed an automated self-checkout security system using OpenCV, FastAPI, image segmentation, and product embeddings to detect theft and miss-scans. Built a workload management system for orchestrating computer vision jobs across GPUs, on-premises and edge clusters, and handheld devices, automating deployment configurations. Created a real-time yard surveillance and alerting system to identify and flag OSHA violations at distribution centers through object detection and knowledge distillation.

Engineer, Computer Vision and AI at Target Corporation

June 1, 2022 - August 23, 2025

Fine-tuned convolutional neural networks (CNNs) for image classification on custom brand photoshoot datasets. Enabled text-to-image search and asset reuse via embedding clustering, cutting search time and saving the design team over $250,000 annually.

Research Assistant at Centre for Artificial Intelligence and Robotics (DRDO)

March 1, 2019 - August 23, 2025

Benchmarked classical machine learning and deep learning models such as Logistic Regression, SVM, Naive Bayes, LSTM, GRU, and Recursive Neural Tensor Networks for sentiment analysis tasks.