自由职业代理评估工程师
Freelance Agent Evaluation Engineer
请提交英文简历并注明您的英语水平。
Mindrift将专家与面向领先科技公司的基于项目的AI机会相连接，专注于测试、评估和改进AI系统。参与方式为项目制，非正式雇佣。
我们正在构建一个数据集来评估AI编码代理——模型如何处理现实中的开发任务。
您将创建具有挑战性的任务和评估标准，这些任务在现实的模拟环境中进行：
- 构建真实的开发环境——一个包含代码库、基础设施和上下文（工单、文档、对话）的虚拟公司，形成可信的开发历史
- 从这些环境的中间状态设计任务——编写提示，定义“解决”的含义，并确保任务可以被AI代理解决
- 编写验证代理解决方案的测试——接受所有有效的方法，拒绝错误的方案，既不过于严格也不过于宽松
- 根据QA反馈迭代任务和测试——审查代理解决方案，分析失败原因，并不断优化直到评估公平且可靠
这并不是：
- 不是数据标注
- 不是提示工程
- 不是从头开始编写代码——代理会编写大部分代码；您负责指导和评估
我们寻找：
- 5年以上软件开发经验
- 核心技术栈：Python（FastAPI）、JavaScript/TypeScript（React）、Docker、Postgres、Kafka、Redis
- 编写测试的经验（功能测试、集成测试）
- 英语水平——B2+
为什么这很难：
前沿模型已经擅长编码。创建真正挑战最优秀模型的任务并不简单。您需要深入理解模型在哪些地方会出错，以及哪些场景能体现出好与坏解决方案的区别。任务有多种有效的解决方案——编写能够接受所有正确方案并拒绝错误方案的测试比听起来要难得多。
要求与福利
教育背景
- 计算机科学、软件工程、数据科学/数据分析、人工智能/机器学习、计算语言学/自然语言处理（NLP）、信息系统或其他相关领域的硕士学位。
- 如果仅候选人有该领域5年工作经验，也接受本科学历。
学术和/或专业经验
候选人应在相关角色或领域至少有3年专业经验——特别是针对QA自动化/测试或网络安全岗位
查看英文原文
Please submit your CV in English and indicate your level of English proficiency.
Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.
We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.
You'll create challenging tasks and evaluation criteria within realistic simulated environments:
- Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history
- Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent
- Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient
- Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust
What this is NOT:
- Not data labeling
- Not prompt engineering
- Not writing code from scratch - the agent writes most of the code; you guide and evaluate
What we look for:
- 5+ years in software development
- Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis
- Experience writing tests (functional, integration)
- English proficiency - B2+
Why this is hard:
Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.
Requirements and benefits
Educational qualifications
- A Master’s Degree in Computer Science, Software Engineering, Data Science / Data Analytics, Artificial Intelligence / Machine Learning, Computational Linguistics / Natural Language Processing (NLP), Information Systems or other related fields.
- Bachelor’s degree is accepted if only candidate has 5 years of experience in the field.
Academic and/or Professional Experience
Candidates should have a minimum of 3 years of professional experience in related roles or domain - specifically for QA-automation/testing or cybersecurity roles
How it works
Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid
Compensation:
Paid per accepted task. Your rate depends on the qualification tier you reach and how efficiently you complete tasks — up to the equivalent of $50/hr. Because payment is per task, a faster pace raises your effective hourly rate.
Why this freelance opportunity might be a great fit for you?
- Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.
- Work on advanced AI projects and gain valuable experience that enhances your portfolio. - Influence how future AI models understand and communicate in your field of expertise.
Originally posted on Himalayas