As a seasoned Machine Learning Engineer with expertise across AI, ML, and Blockchain technologies, I have consistently delivered impactful solutions that drive efficiency and scalability. My work spans designing and deploying ML infrastructures, optimizing model workflows, and integrating AI systems with cloud and edge environments.At AiDash, I streamlined ML workflows by establishing a robust Kubeflow environment, enabling seamless model deployment, distributed training, and drift detection using custom SDK in under 5 lines of code. By building the HILO system, I significantly reduced pipeline deployment complexity, ensuring continuous model monitoring and retraining.At Intel, I optimized ML/DL libraries for OneAPI Analytics Toolkit, improving inference efficiency through model quantization and precision reduction. My work with Intel's Neural Compressor led to a 30% reduction in inference time, directly enhancing client AI solutions.At Accenture, I developed AI solutions (Assembly &Cosmetic Inspection, AutoML) for Defect Detection and video Object Tracking, utilizing cutting-edge Deep Learning models and Google Cloud technologies. I also spearheaded blockchain innovations, contributing to the Hyperledger Bevel project under the Linux Foundation, reducing deployment times for DLT platforms.With a strong foundation in cloud services (GCP), distributed computing, and edge AI solutions, I have a proven track record about leveraging AI technologies to solve complex business challenges, continuously seeking innovative ways to enhance performance and deliver value. Committed to staying at the forefront of AI advancements, exploring emerging technologies like Gen AI and Stable Diffusion Models.
