About me

Hi, I'm Nevin, an AI & Cloud Engineer specializing in ML infrastructure, runtime optimization, and large-scale model deployment across AWS and GCP. I'm passionate about building system-level software for scalable AI acceleration and production reliability. With expertise in Python, C++, Vertex AI, SageMaker, and containerized pipelines, I excel at solving complex problems and optimizing AI systems for impactful business outcomes.

Beyond my technical work, I'm an adventurer and storyteller. I run a YouTube channel where I share my travels and I also love capturing the world through photography. Whether it's developing AI models or framing the perfect shot, I enjoy the process of discovery and innovation. If you share my enthusiasm for AI, cloud engineering, or even just a great adventure story, let's connect!

Ask NevBot anything about me!

Daniel lewis
quote icon

Daniel lewis

Richard was hired to create a corporate identity. We were very pleased with the work done. She has a lot of experience and is very concerned about the needs of client. Lorem ipsum dolor sit amet, ullamcous cididt consectetur adipiscing elit, seds do et eiusmod tempor incididunt ut laborels dolore magnarels alia.

Education

Education

  1. University of Wisconsin - Madison M.S. Data Science 2023 — 2025

    GPA: 3.7/4.0 | Relevant Coursework: Advanced ML, Statistical Analysis, Data Visualization, Big-Data Systems, Optimization

  2. Indian Institute of Information Technology Kottayam B.Tech. Computer Science 2019 — 2023

    GPA: 9.15/10.0 | Relevant Coursework: Statistical Learning, Data Structures, Distributed Systems, Cloud Computing, Algorithms

Experience

Experience

  1. AI Engineer Zion Cloud Solutions – Greater Chicago Area Aug 2025 — Present

    • - Built scalable Vertex AI pipelines improving model deployment speed by 40% and reducing latency 35%.
    • - Engineered Cloud Functions as runtime tools for Gemini LLM, maintaining 99.8% uptime under production load.
    • - Designed client workflows using Pub/Sub and Cloud Run increasing API throughput by 25% overall.
    • - Created RAG-powered custom agents improving automation accuracy by 30% while reducing manual operations 40%.
    • - Optimized system-level runtime containers reducing cloud compute costs 20% across multiple inference workloads.

  2. Data Science Intern Wisconsin School of Business – United States Sep 2024 — Aug 2025

    • - Implemented GPT-3.5 sentiment models identifying 12% negative sentiment increase after major unionization events.
    • - Fine-tuned BERT classifiers improving precision by 18% and reducing API inference cost 25% overall.
    • - Built CLIP-based multimodal price prediction model improving accuracy 23% over previous baselines.
    • - Automated Python-SQL ETL workflows reducing preprocessing time 40% and increasing data reliability significantly.

  3. AI Research Assistant UW–Madison College of Agricultural & Life Sciences – Madison, WI Sep 2024 — Mar 2025

    • - Trained ResNet50 and YOLOv8 models improving detection accuracy 25% and precision 15% through augmentation.
    • - Developed CLIP-based semi-supervised auto-labeling pipeline reducing manual labeling effort 80% overall.
    • - Deployed ML pipelines on AWS SageMaker cutting compute overhead 30% and storage inefficiencies 20%.
    • - Collaborated with growers translating model outputs into actionable insights improving agricultural efficiency.

Publications

Research Publications

  1. An Efficient Stock Price Prediction Mechanism Using Multivariate Sequential LSTM Autoencoder

    Research paper focusing on advanced deep learning techniques for financial market prediction using LSTM autoencoders and multivariate time series analysis.

  2. Advantage Actor-Critic Reinforcement Learning with Technical Indicators for Stock Trading Decisions

    Research paper exploring reinforcement learning applications in algorithmic trading, combining advantage actor-critic methods with technical analysis indicators for improved trading performance.

Certifications

Professional Certifications

  1. Google Cloud Certified – Professional Machine Learning Engineer

    Certified in designing and building production ML systems using Google Cloud technologies, including Vertex AI, AutoML, and MLOps best practices.

  2. AWS Certified Cloud Practitioner (in progress)

    Currently pursuing AWS Cloud Practitioner certification to validate foundational understanding of AWS Cloud concepts and services.

  3. Intro to Machine Learning (Kaggle)

    Completed comprehensive machine learning course covering fundamental concepts, model evaluation, and practical implementation techniques.

  4. Java for Android | Cybersecurity and IoT

    Completed specialized courses in Java for Android development, cybersecurity fundamentals, and Internet of Things (IoT) technologies.

Contact

Contact Form