Yuki is available for hire

Yuki Matoba

Verified Expert in Engineering

DevOps Engineer and Developer

Location

Tokyo, Japan

Toptal Member Since

May 17, 2021

Yuki是一名全栈MLOps和DevOps工程师，在多家公司工作了五年多的经验, from startups to large companies. Yuki作为机器学习工程师和软件开发人员的背景帮助他理解和解决现实世界中的机器学习和软件开发问题.

FastAPI DevOps Engineer AWS DevOps Machine Learning Cloud AIOps Amazon Web Services (AWS)Python Docker Terraform Continuous Delivery (CD)Web Architecture SQL Amazon S3 (AWS S3)GitHub Cisco Meraki

Portfolio

Freelance

Python, Amazon SageMaker, Google BigQuery, Kubernetes, AWS Step Functions...

Cinnamon

Amazon SageMaker, Amazon EKS, Kubernetes, Python 3, Cisco Meraki...

LINE Corp.

Python 3, Kubernetes, TensorFlow, c++， Docker, Amazon EKS...

Experience

Python - 8 years Python 3 - 5 years Scikit-learn - 5 years Amazon SageMaker - 4 years Amazon EKS - 4 years Amazon弹性容器服务(Amazon ECS)——3年 Kubernetes - 3 years

Availability

Part-time

Preferred Environment

亚马逊网络服务(AWS)、Kubernetes、TensorFlow、数据构建工具(dbt)、FastAPI

The most amazing...

...我所做的事情是将SageMaker用于培训，将Seldon用于ML团队的推理，从而节省了70%的模型培训成本和流畅的部署流程.

Work Experience

DevOps | MLOps |机器学习|软件工程师

2020 - PRESENT

Freelance

在Plotly工作，负责Dash Enterprise 5的DevOps/infrastructure.0. 我为Dash Enterprise的Kubernetes集群添加了GPU/Rapids AI支持，并使用vCluster开发CI/CD管道, ArgoCD, and Github Actions.
Contributed to Woven Alpha Inc. (Toyota Research Institute, 并重构了使用AWS Batch制作的超参数调优系统, weights and biases, 并实现了步进函数，实现了标注系统的转换脚本.
为Woven Alpha, Inc .开发了一个大型ETL系统来处理AWS上的培训数据. (丰田研究所，先进开发公司).
为MiddleField公司建立模型和基础设施. 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.
构建模型来预测谁会离开公司去AI CROSS，并使用MLFlow构建环境来开发和评估模型, ECS Fargate, and Kedro.
构建KPI树，并通过SQL分析数据，在Ruby on Rails for React开发的API中实现新算法，对其进行改进, Inc.

Technologies: Python, Amazon SageMaker, Google BigQuery, Kubernetes, AWS Step Functions, AWS Batch, Amazon弹性容器服务(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

Cinnamon

使用EFS在EKS集群上构建一个带有ML(机器学习)模型的SaaS产品, CloudWatch, and so on.
将SageMaker应用于机器学习培训平台. Posted my work on the AWS blog (AWS.amazon.com/blogs/machine - learning/cinnamon ai -保存- 70 ml -模型-培训-成本-亚马逊sagemaker -管理-现场培训).
用EKS、DVC、Seldon、SageMaker等软件设计了一个机器学习培训平台.
基于ISMS管理东京、越南和台湾办公室的内网网络和安全.

Technologies: Amazon SageMaker, Amazon EKS, Kubernetes, Python 3, Cisco Meraki, 资讯保安管理系统(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.

开发了智能设备中的人工智能助手Clova，更多信息可以在Clova找到.line.me.
监督并负责克洛瓦的NLU和对话系统-更多信息可以在Speakerdeck上找到.com/line_developers/nlu-architecture-and-ml-model-management-in-clova.
构建了一个OSS框架来管理在kubernetes上工作的ML模块-更多信息可以在Github上找到.com/rekcurd.
研究并尝试构建一个类似bert的轻量级语言模型.

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

Nyle

用Scala、Spark和CloudSearch开发了一个搜索微服务.
作为SRE(站点可靠性工程师)和公司所有服务的架构师管理AWS.
用Scala和领域驱动设计为新业务开发了一个web应用程序.
负责新工程师的第一阶段面试.

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

Experience

SageMaker training environment

我将SageMaker应用到我们公司的培训基础设施中.
SageMaker现场培训的成本比我们自己的系统低得多, 并且易于管理服务器资源和访问权限.

http://aws.amazon.com/blogs/machine - learning/cinnamon ai -保存- 70 ml -模型-培训-成本-与-亚马逊sagemaker - -现货training/管理

Framework to Manage ML Models on Kubernetes

http://github.com/rekcurd/

Rekcurd是一个管理机器学习(ML)模块的软件包. Rekcurd makes it "easy to serve ML module," "easy to manage and deploy ML models,“和”易于集成到现有服务中." Rekcurd can be run on Kubernetes.

演讲|智能音箱的NLU与对话系统

http://speakerdeck.com/line_developers/nlu-architecture-and-ml-model-management-in-clova

我做了一个关于NLU和Smart Speaker对话系统的演讲. 我通过结合ML模型和基于规则的模型来构建和开发这个模型.

In this presentation, 我解释了整个架构以及如何构建, update, 并在mlop和DevOps方面以较少的努力部署ML模型

Education

2011 - 2015

计算机科学学士学位

俄亥俄北部大学- Ada, OH，美国

Certifications

FEBRUARY 2020 - FEBRUARY 2023

AWS Certified Solutions Architect Associate

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弹性容器服务(Amazon 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, Data Science, 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, Site Reliability Engineering (SRE), Cloud, Load Balancers, FastAPI, 资讯保安管理系统(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

Collaboration That Works

How to Work with Toptal

在数小时内，而不是数周或数月，我们的网络将为您直接匹配全球行业专家.

Share your needs

在与Toptal领域专家的电话中讨论您的需求并细化您的范围.

Choose your talent

在24小时内获得专业匹配人才的简短列表，以进行审查，面试和选择.

Start your risk-free talent trial

与你选择的人才一起工作，试用最多两周. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring