就活ツール
料金プラン

AI Trainer (Data Labeler) – Coding Domain [Traditional Chinese (TW)]

求人情報の更新: 11日前
雇用主は 2日前にアクティブでした

求人内容


We are looking for an AI Trainer (Data Labeler) – Coding Domain with native or professional proficiency in Traditional Chinese (TW). Your role will be to design and review conversation examples that show how AI assistants should interact with users naturally.

No deep AI experience is required – if you can understand basic programming concepts and enjoy logical problem-solving, you’re a great fit! This is a unique chance to join an exciting AI project while growing your technical and communication skills.

  • Write and review short conversations between users and AI assistants.
  • Correct responses only when needed to improve accuracy.
  • Follow clear guidelines; full training provided.
  • Commitments Required: At least 4 hours per day and minimum 20 hours per week
  • Overlap: prefer a few hours overlap with PT for trainings.
  • Engagement Type: Contractor assignment (no medical/paid leave)
  • Duration of Contract: 6 Weeks


応募条件

  • Native or professional proficiency in Traditional Chinese (TW).
  • Basic understanding of programming (e.g., Python, JavaScript).
  • Good written English.

選考プロセス

Once we review your CV and determine that you may be a good fit for the role, we will contact you by email and provide further details about the interview process.

個人用招待リンク
このリンクはあなた専用の求人招待リンクです。リンク経由で誰かが応募するとメールで通知されます。
この求人をシェア
この求人に応募した人は他にこんな求人も応募しています
Logo of the organization.
フルタイム
中上級レベル
1
55K ~ 100K TWD / 月
Logo of the organization.
フルタイム
エントリーレベル
3
応相談
Logo of the organization.
フルタイム
中上級レベル
2
50K ~ 150K TWD / 月
Logo of the organization.
フルタイム
中上級レベル
1
600K ~ 1M TWD / 年
Logo of the organization.
フルタイム
エントリーレベル
2
780K ~ 1.1M TWD / 年
Logo of EBIT Co., LTD.
EBIT Co., LTD
人工知能/機械学習
1~10人 人

私たちについて

EBIT Co., Ltd. is a global talent supply agent founded in 2019, with a mission to drive future innovation through AI technology development. EBIT gathers top talent across Asia and connects them to various projects, primarily focusing on data labeling tasks that contribute to the advancement of AI models.