Platform Engineer (TechLead/Senior Software 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

仕事内容・求める人物像 Position Overview and Who We are Looking For

MLエンジニアが開発した機械学習、深層学習のアセットを容易にデプロイし、スケーラブルなWebAPIとして提供するためのクラウドアーキテクチャーおよびソフトウェアの設計・実装をご担当いただきます。実装にあたっては自身での実装の他、チームメンバーのコードレビューや指導も行っていただきます。

機能拡張の方向性についてはユーザーとの対話を元に、プロダクトマネージャーやチームメンバーと協議しながら決めます。本ポジションの方には、技術的な側面からの意思決定支援を行っていただきます。

このポジションをご担当いただく方へ求めたいこと:

  • 機械学習の社会実装に興味があること
  • コンピューターサイエンスの最新技術に興味があること
  • チームでのソフトウェア開発が得意であること

As a platform senior software engineer, you will be responsible for designing and implementing cloud architecture as well as software to easily deploy and deliver machine and deep learning assets developed by ML engineers as scalable web APIs. As a platform senior software engineer you will be responsible for the code reviews of your team members and providing guidance.

The platform product strategy is determined by team discussions based on the feedback from the platform users and input from other stakeholders. You will be expected to contribute to the team decision from the viewpoint of a senior software engineer.

You are someone who is:

  • Interested in the implementation of machine learning technologies for the sake of solving social issues
  • Interested in cutting edge computer science technologies
  • Good at team development (software)


必須要件 Required Skills

  • 分散処理基盤(Kubernetes/Hadoop等)を活用したスケーラブルな処理基盤の設計、実装経験
  • AWSなどのクラウドプラットフォームを活用した実務開発経験
  • SREやシステム運用の実務経験
  • ソフトウェア開発プロジェクトでのアーキテクチャ設計を含む十分な開発経験
  • git, GitHubの利用経験、及びCI/CDに関する経験
  • 英語のビジネスレベル かつ 日本語の日常会話レベル
      または
    日本語のビジネスレベル かつ 英語の読み書きができるレベル

  • Experience designing and implementing scalable processing infrastructure utilising distributed processing infrastructure (Kubernetes/Hadoop, etc.)
  • Development experience utilising AWS or other cloud platforms
  • Practical experience in SRE and system operation
  • Experience in software development projects, including architectural design
  • Experience with git, GitHub, and CI/CD
  • Effective interpersonal and communication skills :

  Business-level English and conversational Japanese
  OR
  Business-level Japanese and at least reading and writing capabilities for English


歓迎要件 Preferred Skills

  • 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
  • プロジェクトマネジメントスキル
  • プロダクトやサービスの開発経験
  • スタートアップ環境での勤務経験
  • 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)
  • 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

  • Background in computer science or a related field
  • Project management skills
  • Product and service development experience
  • Experience working in a startup environment
  • Understanding of machine learning frameworks (Scipy/Numpy, Scikit-Learn, Pandas, Tensorflow/Keras/PyTorch)
  • Understanding of machine learning models in a business environment (linear regression, ensemble learning, boosting, RNN, CNN, GCN, GAN, etc.)
  • Strong initiative in a business setting to lead a team/organisation


選考フロー Screening Process

▼Documentation Check (Resume & Test)
▼1st Interview
▼2nd Interview
▼Final Interview

  • 応募する

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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