Arbaaz Dharmavaram
AI Engineer @ agentiiv
About
I am a Full Stack ML Engineer and Researcher who bridges the gap between academic theory and production-grade software. I recently graduated with my Master's in CS (Oct 2025), where my research focused on detecting misinformation and building AI systems that are trustworthy and verifiable. My background covers the full AI lifecycle across multiple domains: - Enterprise Experience: Previously at Target, I developed patented edge AI algorithms for detecting theft at self-checkouts and enforcing safety compliance (OSHA) in resource-constrained environments. - Threat Intelligence: At the Canadian Institute for Cybersecurity, I developed Agentic and RAG workflows for threat intelligence and vulnerability management. - Research: My academic work involved fine-tuning LLMs using RLHF and quantizing for efficiency, resulting in publications at ACL-FEVER 2025 and PST 2025. - Grant Intelligence: During my time at the Vector Institute, I engineered multi-agent systems, Memory and Graph RAGs to monitor government grant portals and automate grant application drafting I am always on the lookout for work that challenges me, allowing me to apply my experience in software engineering, ML, agentic workflows, and system design to build scalable products. Tech Stack: Python, JavaScript, PyTorch, LangGraph, Google ADK, Docker/Kubernetes and Azure. Research & Code: https://scholar.google.ca/citations?user=NDd_VI8AAAAJ&hl=en https://github.com/arbaaz-abz Music Production: https://www.youtube.com/DmArbaaz I also happen to make music: https://www.youtube.com/DmArbaaz
Canada
Toronto
Higher Education
AI SDK, Node.js, React.js, RAG, Microsoft Azure, Data Pipelines, Large Language Models (LLM), Multi-agent Systems, Information Retrieval, Fact Checking, docker, FastAPI, PostgreSQL, Natural Language Processing (NLP), Python, Web Development, Machine Learning, Deep Learning, Computer Vision, Flask
Experience
AI Engineer
agentiiv
Toronto, Ontario, Canada
Multi-agent AI systems, at the intersection of agentic workflows, data engineering, and LLM Observability/Evaluations.
Machine Learning Engineer
Vector Institute
Toronto, Ontario, Canada
FASTLANE 2025 Fall: Building Multi-agentic systems with long-horizon task coherence and shared memory
Software Engineer
Canadian Institute for Cybersecurity
Fredericton, New Brunswick, Canada
Developed AI-driven tools that provide organizational-level vulnerability management and threat prioritization leveraging open-source threat intelligence. Built an agentic GenAI pipeline integrating search capabilities with RAG, automating cybersecurity reporting with PostgreSQL and Power BI dashboards.
Graduate Teaching Assistant
University of New Brunswick
Fredericton, New Brunswick, Canada
Tutoring undergrad students in Racket, JavaScript and Python.
Senior Software Engineer
Target
Bengaluru, Karnataka, India
Software Engineer
Target
Bangalore, India
Building solutions using Computer Vision & A.I to solve high valued business problems in the domain of retail. Responsibilities: •Research and experimenting with building, training and deploying state of the art Deep learning models. •My work also touches upon the infrastructure aspects on development including designing, building and deploying end-to-end data curation, data aggregation pipelines, APIs etc. Projects: - Built object detection & classification models to extract the most relevant objects and labels from the underlying brand deal images and group them, saving Target several Million $'s every year on image searching by reusability. - Built a consolidated web application that showcases all our platforms CV capabilities in an interactive manner to other tenant portfolio teams. - Detection of Ticket switching, miss-scans by customers in real-time at self-checkout counters using Machine Learning and Deep learning models. - Monitoring and detecting Safety violation incidents in real-time at Target’s Distribution centres, using Object detection, Tracking and notification alerts.
Software Engineer
Ugam
Bangalore Urban, Karnataka, India
• Developed propensity models to analyze customer behavior, enhancing coupon recommendation strategies. • Designed and implemented customer brand pages for various retail firms, improving user engagement. • Leveraged Apache Spark and Python for data processing and machine learning applications, optimizing performance.
Project Trainee
Center For Artificial Intelligence And Robotics
Bangalore
Benchmarked ML and deep learning models (e.g., LSTM, GRU) for Twitter sentiment analysis to support social media intelligence tasks.
Education
University of New Brunswick
Computer Science
Udacity
Artificial Intelligence
Completed the Nanodegree on Computer Vision from Udacity (Span of Three months). Worked on many projects spanning from OpenCV, CNNs, LSTMs, Attention Mechanisms, Image Captioning and Robot Navigation
Arbaaz Dharmavaram's Contact Information
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