Innovative ML Scientist 🚀 | Problem-Solver 💡 | Lifelong Learner 📚I’m an experienced Machine Learning Scientist with over 4 years of expertise in designing and implementing impactful ML solutions across industries such as semiconductor, e-commerce, edge-device, and healthcare. At Intel, I optimized the schedule of applying OS patches/fixes to hosts, and reduced resource waste by 60% through predictive modeling. I also enhanced model deployment speeds tenfold with a scalable MLOps framework. My tenure at Amazon involved migrating over 90 machine learning models (for Ads) into production with zero downtime, while at Motorola, I led the development of a personalized recommendation system that boosted click-through rates by 20%.I hold a Master’s degree in Computer Science from the University of Southern California, graduating with Honors and a 4.0 GPA. During my time there, I contributed to cutting-edge research in neuroimaging and multimodal deep learning, further honing my skills in data science. I was also recognized with the prestigious CSCI MS Honors & Scholarship for my academic performance. My undergraduate studies were completed with distinction, ranking third in my class at Sri Jayachamarajendra College of Engineering.Certified in key ML frameworks such as PyTorch, TensorFlow, and scikit-learn, I am proficient in managing end-to-end machine learning pipelines using tools like AWS SageMaker, MLflow, and Docker. My skills also extend to cloud computing with hands-on experience in AWS, GCP, and Azure, as well as deploying generative AI models and building sophisticated data pipelines.I am driven by the challenge of solving complex problems and creating business impact through data-driven innovation. I am now looking to apply my expertise in a forward-thinking environment, driving machine learning advancements to deliver measurable outcomes.Let's connect and explore how we can combine our expertise to unlock new horizons in technology and innovation.