Yuki Matoba
Verified Expert in Engineering
DevOps Engineer and Developer
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.
Portfolio
Experience
Availability
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
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.
Infrastructure Manager
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.
Software Engineer
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.
Software and Infrastructure Engineer
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.
Experience
SageMaker training environment
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/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-clovaIn 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
Skills
Languages
Python 3, Python, SQL, JavaScript, c++, Ruby, TypeScript, PHP 7, Scala, Lustre
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
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
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
Frameworks
Ruby on Rails 4, Ruby on Rails (RoR), Spark
Education
计算机科学学士学位
俄亥俄北部大学- Ada, OH,美国
Certifications
AWS Certified Solutions Architect Associate
AWS
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