Bogs Espinas
Machine Learning Engineer focused on building end-to-end machine learning pipelines and operationalizing machine learning models
About
As a Machine Learning Engineer, I have built prediction and monitoring pipelines, developed web applications to centralize machine learning operations, and developed internal guidelines or frameworks to operationalize Reinforcement Learning models.
Work Experience
GCash
2023 - present
Lead, Machine Learning Operations Engineer
Built a centralized platform for observability and monitoring of Machine Learning models. Orchestrated ML workflows using Airflow, Sagemaker, and Kubernetes. Deployed ML models in various environments using CI/CD. Performed incident management and root cause analysis to ensure system and model reliability.
Kumu
2022 - 2023
Software Engineer II
Built microservices that scales to thousands of users using Golang, Redis, Docker, AWS, and Kubernetes.
Demand Science
2021 - 2022
Software Engineer
Built dashboards using Django, DynamoDB, and React. Built data quality pipelines using Golang and GraphQL.
Senti AI
2019 - 2021
Software Engineer
Built a COVID-19 info chatbot for the government using Node.js, GCP, and DialogFlow. Built an anomaly detection engine for a telecommunications company using Python, Sklearn, and AWS
Education
Ateneo de Naga University
2015 - 2019
Bachelor of Science in Information Technology (Cum Laude)
Certification
AWS Certified Developer - Associate
2022 - 2025
Amazon Web Services
Skills
Python
Golang
FastAPI
Gin
Redis
Postgres
Kubernetes
Docker
AWS
Airflow
Alibaba MaxCompute
MLOps
Projects
Introduction to K8s
github.comjrpespinas/intro-to-k8s
A simple REST API deployed to a kubernetes cluster--locally using minikube
Minikube
Kubernetes
Docker
FastAPI
Introduction to CI/CD
github.comjrpespinas/intro-to-cicd
A simple REST API image published to docker hub using CI/CD practices with Github Actions
Github Actions
Docker
FastAPI