Yuki Matoba
Verified Expert in Engineering
DevOps Engineer and Developer
Tokyo, Japan
Toptal member since May 17, 2021
Yuki is a full-stack MLOps and DevOps engineer with over five years of experience working for various companies, from startups to large companies. Yuki's background as a machine learning engineer and a software developer helps him understand and solve real-world machine learning and software development problems.
Portfolio
Experience
- Python - 8 years
- Python 3 - 5 years
- Scikit-learn - 5 years
- Amazon SageMaker - 4 years
- Amazon EKS - 4 years
- Amazon Elastic Container Service (ECS) - 3 years
- Kubernetes - 3 years
Work Experience
DevOps | MLOps | Machine Learning | Software Engineer
Freelance
- Worked for Plotly and was in charge of DevOps/infrastructure of Dash Enterprise 5.0. I added GPU/Rapids AI support to the Kubernetes cluster of Dash Enterprise and worked on CI/CD pipeline with vCluster, ArgoCD, and Github Actions.
- Contributed to Woven Alpha Inc. (Toyota Research Institute, Advanced Development Inc) and refactored the hyperparameter tuning system made with AWS Batch, weights and biases, and step functions and implemented the labeling system's conversion scripts.
- Developed a large ETL system to deal with training data on AWS for Woven Alpha, Inc. (Toyota Research Institute, Advanced Development Inc).
- Built models and infrastructure for MiddleField Inc. to offer personalized items using Amazon Personalize and SageMaker; implemented the model infrastructure environment to predict prices of used cars by using Kubeflow pipelines and Seldon Core.
- Constructed models to predict who leaves companies for AI CROSS and built the environment to develop and evaluate models using MLFlow, ECS Fargate, and Kedro.
- Built a KPI tree and improved it by analyzing data with SQL and implementing the new algorithm in API developed by Ruby on Rails for React, Inc.
Infrastructure Manager
Cinnamon
- Built a SaaS product with ML (machine learning) models on EKS cluster using EFS, CloudWatch, and so on.
- Applied SageMaker for an ML training platform. Posted my work on the AWS blog (AWS.amazon.com/blogs/machine-learning/cinnamon-ai-saves-70-on-ml-model-training-costs-with-amazon-sagemaker-managed-spot-training).
- Designed an ML training platform with EKS, DVC, Seldon, SageMaker, and so on.
- Managed an intranet network and security in the Tokyo, Vietnam, and Taiwan offices based on ISMS.
Software Engineer
LINE Corp.
- Developed Clova, an AI assistant in smart devices—more information can be found at Clova.line.me.
- Oversaw and was in charge of the NLU and dialog system in Clova—more information can be found at Speakerdeck.com/line_developers/nlu-architecture-and-ml-model-management-in-clova.
- Constructed an OSS framework to manage ML modules working on Kubernetes—more information can be found at Github.com/rekcurd.
- Researched and experimented with building a BERT-like lightweight language model.
Software and Infrastructure Engineer
Nyle
- Developed a search microservice in Scala, Spark, and CloudSearch.
- Managed AWS as an SRE (site reliability engineer) and architect for all services in the company.
- Developed a web application for new business in Scala and domain-driven design.
- Conducted the first stage interviews for new engineers.
Project History
SageMaker training environment
SageMaker spot training costs much less than our own system, and it is easy to manage server resources and access permissions.
https://aws.amazon.com/blogs/machine-learning/cinnamon-ai-saves-70-on-ml-model-training-costs-with-amazon-sagemaker-managed-spot-training/
Framework to Manage ML Models on Kubernetes
https://github.com/rekcurd/Presentation | NLU and Dialog System of Smart Speaker
https://speakerdeck.com/line_developers/nlu-architecture-and-ml-model-management-in-clovaIn this presentation, I explained the whole architecture and how to build, update, and deploy ML models with less effort in terms of MLOps and DevOps
Education
Bachelor of Science Degree in Computer Science
Ohio Northern University - Ada, OH, United States
Certifications
AWS Certified Solutions Architect - Associate
Amazon Web Services (AWS)
Skills
Libraries/APIs
Scikit-learn, Node.js, React, TensorFlow, PyTorch
Tools
Amazon SageMaker, Amazon EKS, AWS CloudFormation, Terraform, GitHub, Ansible, Docker Compose, Amazon Virtual Private Cloud (VPC), AWS Step Functions, AWS Batch, Amazon Elastic Container Service (ECS), Grafana, Jenkins, VPN, Helm, Cisco Meraki, GitLab, GitLab CI/CD, NGINX, Apache, Postfix, RabbitMQ, Travis CI
Languages
Python 3, Python, SQL, JavaScript, C++, Ruby, TypeScript, PHP 7, Scala, Lustre
Paradigms
Web Architecture, DevOps, Continuous Integration (CI), Continuous Delivery (CD), Continuous Development (CD), ETL, Microservices
Platforms
Docker, Amazon Web Services (AWS), Linux, Amazon EC2, Kubernetes, Google Cloud Platform (GCP), OpenShift, CentOS, Apache Kafka, Windows Server
Storage
Web SQL, MySQL, Amazon S3 (AWS S3), Redis, Google Cloud, PostgreSQL, MongoDB
Frameworks
Ruby on Rails 4, Ruby on Rails (RoR), Spark
Other
Software Deployment, AIOps, CI/CD Pipelines, DevOps Engineer, AWS DevOps, Machine Learning, Data Science, Site Reliability Engineering (SRE), Cloud, Load Balancers, FastAPI, Information Security Management Systems (ISMS), Google BigQuery, Natural Language Processing (NLP), Prometheus, GBM, HAProxy, Build Pipelines, GitHub Actions, API Design, Generative Pre-trained Transformers (GPT), Data Build Tool (dbt), Dagster, Amazon CloudSearch, Optical Character Recognition (OCR), Argo CD, SaaS, Amazon RDS
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