Yuki Matoba, Developer in Tokyo, Japan
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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.


Python, Amazon SageMaker, Google BigQuery, Kubernetes, AWS Step Functions...
Amazon SageMaker, Amazon EKS, Kubernetes, Python 3, Cisco Meraki...
LINE Corp.
Python 3, Kubernetes, TensorFlow, C++, Docker, Amazon EKS...




Preferred Environment

Amazon Web Services (AWS), Kubernetes, TensorFlow, Data Build Tool (dbt), FastAPI

The most amazing...

...thing I've done was apply SageMaker for training and Seldon for inference to the ML team and save 70% on model training costs and fluent deployment flow.

Work Experience

DevOps | MLOps | Machine Learning | Software Engineer

2020 - PRESENT
  • 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.
Technologies: Python, Amazon SageMaker, Google BigQuery, Kubernetes, AWS Step Functions, AWS Batch, Amazon Elastic Container Service (Amazon ECS), TensorFlow, Google Cloud Platform (GCP), Ruby, Ruby on Rails 4, Docker, AWS CloudFormation, Amazon Web Services (AWS), CI/CD Pipelines, SQL, DevOps Engineer, AWS DevOps, DevOps, Grafana, MySQL, Prometheus, Machine Learning, ETL, Amazon S3 (AWS S3), Data Science, GitHub, Google Cloud, GBM, GitLab, GitLab CI/CD, Continuous Integration (CI), Ansible, MongoDB, Continuous Delivery (CD), Site Reliability Engineering (SRE), Ruby on Rails (RoR), NGINX, Cloud, React, TypeScript, Amazon EC2, Jenkins, Redis, Node.js, Continuous Development (CD), Build Pipelines, GitHub Actions, API Design, JavaScript, Amazon Virtual Private Cloud (VPC), Docker Compose, Helm, Data Build Tool (dbt), Dagster, FastAPI

Infrastructure Manager

2019 - 2020
  • 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.
Technologies: Amazon SageMaker, Amazon EKS, Kubernetes, Python 3, Cisco Meraki, Information Security Management Systems (ISMS), Docker, AIOps, Amazon Web Services (AWS), SQL, AWS CloudFormation, CI/CD Pipelines, DevOps, DevOps Engineer, AWS DevOps, Grafana, Prometheus, Linux, OCR, Machine Learning, Amazon S3 (AWS S3), GitHub, Ansible, PostgreSQL, Continuous Integration (CI), Continuous Delivery (CD), Site Reliability Engineering (SRE), Argo CD, SaaS, MongoDB, NGINX, Cloud, Redis, Amazon EC2, Amazon RDS, CentOS, Jenkins, RabbitMQ, Apache Kafka, Windows Server, VPN, Continuous Development (CD), Build Pipelines, GitHub Actions, Docker Compose, Amazon Virtual Private Cloud (VPC), Helm

Software Engineer

2018 - 2019
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.
Technologies: Python 3, Kubernetes, TensorFlow, C++, Docker, Amazon EKS, Amazon Web Services (AWS), SQL, Python, AWS CloudFormation, DevOps, AWS DevOps, DevOps Engineer, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Machine Learning, Data Science, Amazon S3 (AWS S3), GitHub, Terraform, Ansible, Continuous Integration (CI), Microservices, Cloud, React, Travis CI, API Design, JavaScript, PyTorch, Data Build Tool (dbt), FastAPI

Software and Infrastructure Engineer

2015 - 2017
  • 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.
Technologies: PHP 7, Scala, Scikit-learn, Amazon CloudSearch, Spark, SQL, Amazon Web Services (AWS), Terraform, CI/CD Pipelines, Web SQL, DevOps, AWS DevOps, DevOps Engineer, Machine Learning, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), GPT, GitHub, OpenShift, Continuous Integration (CI), Ansible, PostgreSQL, Site Reliability Engineering (SRE), Microservices, Continuous Delivery (CD), NGINX, Cloud, HAProxy, Redis, Apache, Amazon EC2, Amazon RDS, CentOS, Load Balancers, Postfix, Node.js, Build Pipelines, Continuous Development (CD), API Design, JavaScript, Amazon Virtual Private Cloud (VPC), Docker Compose

SageMaker training environment

I applied SageMaker to training infrastructure of our company.
SageMaker spot training costs much less than our own system, and it is easy to manage server resources and access permissions.


Framework to Manage ML Models on Kubernetes

Rekcurd is a software package for the management of machine learning (ML) modules. Rekcurd makes it "easy to serve ML module," "easy to manage and deploy ML models," and "easy to integrate into the existing service." Rekcurd can be run on Kubernetes.

Presentation | NLU and Dialog System of Smart Speaker

I made a presentation about the NLU and dialog system of Smart Speaker. I architected and developed this by combining ML models and a rule-based model.

In 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
2011 - 2015

Bachelor of Science Degree in Computer Science

Ohio Northern University - Ada, OH, United States


AWS Certified Solutions Architect Associate



Scikit-learn, Node.js, React, TensorFlow, PyTorch


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 (Amazon ECS), Grafana, Jenkins, VPN, Helm, Cisco Meraki, GitLab, GitLab CI/CD, NGINX, Apache, Postfix, RabbitMQ, Travis CI


Python 3, Python, SQL, JavaScript, C++, Ruby, TypeScript, PHP 7, Scala, Lustre


Web Architecture, DevOps, Data Science, Continuous Integration (CI), Continuous Delivery (CD), Continuous Development (CD), ETL, Microservices


Docker, Amazon Web Services (AWS), Linux, Amazon EC2, Kubernetes, Google Cloud Platform (GCP), OpenShift, CentOS, Apache Kafka, Windows Server


Web SQL, MySQL, Amazon S3 (AWS S3), Redis, Google Cloud, PostgreSQL, MongoDB


Ruby on Rails 4, Ruby on Rails (RoR), Spark


Software Deployment, AIOps, CI/CD Pipelines, DevOps Engineer, AWS DevOps, Machine Learning, 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, GPT, Generative Pre-trained Transformers (GPT), Data Build Tool (dbt), Dagster, Amazon CloudSearch, OCR, Argo CD, SaaS, Amazon RDS

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