出海雷达

高级提示工程师(法国)

Senior Prompt Engineer (France)

AI开发工程限定地区(需当地身份)日间重叠约 2 小时,需偶尔早起或晚睡
公司Welo Global
薪资未公开
工作地点France
地域资格限定地区(需当地身份)
时区要求日间重叠约 2 小时,需偶尔早起或晚睡
用工类型permanent
发布时间2026-05-30
数据来源4dayweek.io
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注意地域限制:该职位明确限定在 France 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。
作息提示:日间重叠约 2 小时,需偶尔早起或晚睡。

We are seeking a Prompt Engineer to be responsible for the end-to-end technical migration workflow for transitioning templates to LLM autoraters. The role is required to use client’s internal tools to leverage prompt engineering techniques to maximize model performance.

Responsibilities:
Utilize Automatic Prompt Generation (APG) tools to create baseline prompts for complex parent-child template clusters.

Run and supervise Automated Prompt Optimization (APO) tool, review the outputs, and flag when the APO reaches deadlocks or plateaus.

Manually draft, test, and refine prompts to navigate complex template architectures, overcome anti-patterns, and handle edge cases where tooling is lacking or broken. Solve edge-case scenarios by designing and refining manual prompts.

Monitor shadowbot runs to ensure sufficient disagreements (between human and LLM ratings) are registered, generated, and tracked.

Run prompt versions against established gold data to continuously measure autorater quality against the human crowd baseline, calculating accuracy metrics such as F1 scores, precision, and recall.

Draft technical launch readiness justifications (Launch Certification Documentation) for final.

Requirement:
Language Skills: Native fluency in French and fluent in English.

Location: Must be based in France.

Education: Bachelor’s, Master’s, or Doctorate degree in Computer Science, Data Science, Computational Linguistics, Human-Computer Interaction (HCI), Cognitive Science, or a related analytical field.

Prompt Engineering & AI Expertise: At least 4 years' experience as Prompt Engineer. Proven experience tuning Large Language Models (LLMs) for strict, structured outputs, complex classification tasks, and familiarity with chain-of-thought and few-shot learning.

Data Analysis: Strong proficiency in identifying error patterns, analyzing model performance, and using SQL or other data analytics tools.

Technical Agility: Ability to quickly learn and master proprietary tools with minimal supervision.

Communication: Excellent verbal and written communication skills.

Optional / Preferred Skills:
Familiarity with enterprise-grade LLM interfaces like the Goose API.

Experience in AI model evaluation, data science, computational linguistics, or software engineering.

Hands-on experience with Automated Prompt Optimization (APO) systems or tuning workflows.

Linguistic expertise, including an understanding of semantics and logic.

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