Welcome to my GitHub profile! This is Kennedy Antonio, a Senior machine learning ՄMLՅ engineer with 8 years of experience in the research, development, and application of various ML, AI, and generative AI solutions. I have turned big data into valuable actions and have a demonstrated history of driving business efficiencies and cost reductions. I am proficient in generative AI, prompt engineering, computer vision, natural language processing ՄNLPՅ, anomaly detection, and prediction tasks.

• API Development: Experience in developing and maintaining APIs for seamless integration of services.
• Machine Learning: Experience in Artificial Intelligence(LLM, Generative AI, Computer Vision, Data Analytics).
• Full Stack development: Frontend and Backend development(JS/TS, Python).
• Cloud Infrastructure Management: Expertise in AWS, Azure, and Google Cloud platforms.
• Container Orchestration: Proficient in Docker and Kubernetes for managing and scaling containerized applications.
• CI/CD Pipelines: Skilled in creating and optimizing CI/CD pipelines to streamline deployments and enhance development workflows.

2023 - 2024
Maryland, US (Remote)

• Led the development and operationalization of voice and video analysis product offerings, managing the full stack of advanced analytics and machine learning ՄMLՅ pipelines.
• Architected, built, and deployed the Comcast Machine Learning Infrastructure, enabling inference for Xfinity Home Security cameras. Utilized TensorFlow object detection models on AWS EKS/Kubernetes, achieving a 30% reduction in inference time. Implemented Prometheus and Grafana for enhanced observability, resulting in a 25% increase in system uptime.
• Designed and executed observability and monitoring capabilities for the Comcast Xfinity Voice Assistant Platform, which serves millions of customers. Leveraged machine learning and cloud technologies to process over 1 billion natural language queries, improving query response accuracy by 15%
• Conducted R&D on machine learning models for anomaly detection in Comcast Xfinity Home Security systems, utilizing various home sensor events (e.g., motion, door, window, Wi-Fi connections). This work led to a 20% improvement in anomaly detection rates.
• As a Machine Learning R&D Engineer at Comcast, I developed models to detect anomalous network events, enhancing operational efficiency by 30% within the Network Product and Services Division.
• Formulated predictive models to improve child support collection activities and monitor children's health and safety in foster care. Oversaw the project as the Lead Machine Learning Engineer, achieving a 40% increase in successful collections and a 25% improvement in safety monitoring outcomes.

2019 - 2023
Manila, Philippines (On-site)

• Developed an NLP-powered engine to classify the root causes of millions of machine text log messages, significantly improving tool utilization and saving over 1,500 labor hours annually at Intel fabs. Built a robust Python text data processing pipeline to ingest data from an Elasticsearch API, enhancing data accessibility and analysis speed by 40%.
• Constructed a computer vision anomaly detection solution at Intel to enhance tool availability and address maintenance quality issues. Leveraging object detection and deep learning, I achieved a 30% reduction in downtime and improved response times by 25%, while enhancing image quality and processing efficiency
• Spearheaded the development of a Machine Learning Operations ՄMLOps) framework at Intel, enabling rapid and scalable AI/ML deployments. This initiative achieved a 50% increase in deployment speed and a 35% enhancement in model performance monitoring across global products and factories.

2017 - 2019
Manila, Philippines (On-site)

• Engineered machine learning and analytics software for the simulation and enhanced operation of advanced renewable energy storage systems, resulting in a 15% increase in energy efficiency and a 20% reduction in operational costs.
• Shaped and deployed energy market trading optimization algorithms and applications, improving trading performance by 25% and increasing revenue generation capabilities.
• Created monitoring reports utilizing in-memory caching, enabling real-time data updates every second, which enhanced user experience and decision-making speed by 30%.
• Optimized customer resource allocation, achieving a 20% reduction in turnaround time for service requests, leading to advanced customer satisfaction scores.
• Conducted root cause analysis for over 10 critical issues, identifying bugs and implementing fixes in production within 24 hours, which minimized downtime and boosted system reliability by 40%.

• Fiverr Bug Bounty - Recognized for identifying and reporting critical vulnerabilities.
• VestaCp Bug Bounty - Awarded for contributions to improving security.

• Mindanao State University
  Bachelor's degree in Computer Science (March 2012 - April 2016)

• Cloud Platforms: AWS, Azure, Google Cloud
• Containerization: Docker, Kubernetes
• CI/CD Tools: GitLab CI, GitHub Actions, Jenkins
• API Development: REST, GraphQL
• Programming Languages: Python, C++, JS/TS
• Machine Learning: TensorFlow, Keras, PyTorch, Generative AI, Reinforce learing, Matlab
• Data Analytices: PySpark, Power BI, Matplotlib, DataBrick, ElasticSearch, Warehouse
• Web Technologies: React, Next.js, Python Django/Flask, Node.js, MongoDB, Redis, PostgreSQL, SQL, Dynamo DB