AI Solution Architect & Consultant

Spearheaded Agentic AI initiatives, guiding multiple clients from conceptualization to successful Proof-of-Concept (PoC) and Minimum Viable Product (MVP) deployments, significantly accelerating AI adoption strategies.

Architected and implemented complex AI solutions across diverse domains, including Computer Vision for automotive applications, NLP for document classification, and Reinforcement Learning for industrial process optimization.

Provided comprehensive AI advisory services, conducting AI audits, developing best practices, and formulating data-driven strategies that resulted in a 25% improvement in client project efficiency and ROI.

Secured and contributed to multiple patents in Automotive AI and Computer Vision, demonstrating innovative problem-solving and establishing intellectual property in highly competitive markets.

Managed end-to-end AI project lifecycles, ensuring seamless integration of models, robust data pipelines, and scalable deployment strategies that enhanced operational capabilities for enterprise clients.

Designed and implemented a Reinforcement Learning system for optimizing industrial water processes, leading to a 15% reduction in energy consumption and a 10% improvement in water quality metrics.

Developed and integrated traditional ML models with IoT sensor data, enabling predictive maintenance that reduced unscheduled downtime by 20% across manufacturing facilities.

Collaborated with cross-functional engineering teams to translate operational challenges into scalable AI solutions, improving system efficiency and reducing operational costs by an average of $500K annually.

Pioneered the application of machine learning techniques to enhance sensor data analysis, improving data accuracy by 30% and providing more reliable inputs for critical decision-making.

Developed advanced Computer Vision algorithms for autonomous driving features, contributing to a 98% accuracy rate in object detection and classification in diverse environmental conditions.

Authored and secured multiple patents in the Automotive AI domain, specifically for novel approaches to real-time image processing and sensor fusion, enhancing vehicle safety systems.

Implemented Document Classification systems using NLP techniques, including FastText, to process and categorize vast amounts of unstructured text data, improving information retrieval efficiency by 40%.

Contributed to the development of a proprietary ML model training pipeline, reducing model iteration cycles by 25% and accelerating the deployment of new AI features into prototypes.