Fullstack Machine Learning Engineer

  • Tokyo
  • Remote OK
  • Full-time
  • December 23, 2023
Conditions
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Apply from Anywhere 👍
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Relocation to Japan 👍
(Overseas visa sponsorship supported)
Requirements
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Language Requirements
Japanese: Conversational
English: Business Level
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Minimum Experience
Mid-level or above

Role 仕事内容

  • Develop ML/NLP applications on top of our core machine learning assets.
  • Architect and develop a scalable cloud AI service.
  • 機械学習・深層学習のアセット上でのアプリケーションの開発
  • AIサービスをスケーラブルに提供するためのクラウドアーキテクチャーの設計・構築

Minimum Skill/Experience 必須要件

  • Strong background in Computer Science or a related field
  • Extensive experiences in application development
  • Working experiences with AWS or other cloud platforms
  • Strong experiences with ML frameworks such as Scipy/Numpy, Scikit-Learn, Pandas, Tensorflow/Keras/PyTorch
  • Good working knowledge of machine learning models (linear regression, ensemble methods, boosting, RNN, CNN, GCN, GAN, etc.)
  • Experiences with git, GitHub, CI/CD
  • Good communication skill

-コンピューターサイエンスまたは周辺領域のバックグラウンド
-アプリケーション開発に精通した経験
-AWSなどクラウドプラットフォーム上での実務開発経験
-機械学習フレームワークへの理解(Scipy/Numpy, Scikit-Learn, Pandas, Tensorflow/Keras/PyTorch)
-ビジネス環境における機械学習モデルの理解(線形回帰, アンサンブル学習, boosting, RNN, CNN, GCN, GANなど)
-git, GitHubの利用経験、及びCI/CDに関する経験
-日本語または英語の十分なコミュニケーションスキル

Preferred Skill/Experience 歓迎要件

  • Experience with working at startups
  • Strong work initiative

-スタートアップ環境での勤務経験
-チーム/組織をリードするビジネスシーンでの強いイニシアチブ

ExaWizards is an AI start-up with a simple mission: solve social issues using AI and create a happy society. But to achieve it, they’re tackling issues across a wide variety of industries: Care tech, HR, fintech, medicine, security and more. They believe AI can help solve problems in all these areas, and they’re determined to do just that. Their business model can be broken into two different flows: project-focused and product-focused. For project-focused initiatives, they start from scratch. Their ML engineers and consultants identify business problems and build models aimed at solving them. In their product flow, they take the ML models developed for specific problems and generalize them to be useful for a wider array of problems. Normally they develop these solutions into SaaS products.

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Fullstack Machine Learning Engineer at ExaWizards
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