Machine Learning Engineer
- Tokyo
- Remote OK
- Full-time
- December 23, 2023
【技術で社会課題を解決する】機械学習エンジニア募集!
Role 仕事内容
・Research and implement state-of-the-art ML models
・Solve problems provided by our partner companies (large corporations)
・大手企業と連携した研究/ソリューション開発
・機械学習の研究/アルゴリズム実装
Minimum Skill/Experience 必須要件
・Strong knowledge of Python
・Experience with ML frameworks such as Scipy/Numpy, Scikit-Learn, Pandas, Tensorflow, ・Keras, Chainer, PyTorch
・Strong knowledge of Computer Science or related quantitative field
・Strong knowledge of machine learning models (linear regression, ensemble methods, boosting, RNN, CNN, GCN, GAN, etc.)
・Ability to implement models from papers
・Demonstrated history of model research and design
・Experience with git/hg
・Good communication skill (Japanese)
・Pythonの深い理解と豊富な知識
・Scipy/Numpy, Scikit-Learn, Pandas, Tensorflow, Keras, Chainer, PyTorchなどのフレームワークを利用した機械学習における実装経験
・機械学習の理論的背景を理解
・機械学習のモデルの理解(線形回帰, アンサンブル学習, 勾配ブースティング, RNN, CNN, GCN, GAN, YOLOなど)
・論文のモデルを実装する能力
・自らモデルをデザイン・研究・実装していく姿勢
・高いコミュニケーションスキル(日本語)
Preferred Skill/Experience 歓迎要件
・Good communication skill (English)
・Strong knowledge of algorithms and data structures
・Experience with working at startups
・Strong work initiative
・高いコミュニケーションスキル(英語)
・Git, hgといった開発環境での経験
・アルゴリズムやデータ構造の知識
・スタートアップで働いた経験
・新しい課題や未知の領域に果敢に挑戦した経験
面接プロセス
▼書類選考
▼電話・オンラインインタビュー
▼一次面接(コーディングインタビュー)
▼二次面接
▼最終面接
▼内定
▼オファー面談
※場合によって選考回数は増減します。
About ExaWizards
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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