<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <em>Please submit your CV in English and indicate your level of English proficiency.<br/><br/></em>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. <strong>Participation is project-based, not permanent employment.<br/><br/></strong><strong>What This Opportunity Involves<br/><br/></strong>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br/><br/>You'll create challenging tasks and evaluation criteria within realistic simulated environments:<br/><br/><ul><li>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history</li><li>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</li><li>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient</li><li>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust<br/><br/></li></ul><strong>What This Is NOT<br/><br/></strong><ul><li>Not data labeling</li><li>Not prompt engineering</li><li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate<br/><br/></li></ul><strong>What We Look For<br/><br/></strong><ul><li>5+ years in software development</li><li>Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis</li><li>Experience writing tests (functional, integration)</li><li>English proficiency - B2+<br/><br/></li></ul><strong>Why this is hard <br/><br/></strong>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.<br/><br/><strong>How It Works<br/><br/></strong>Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid<br/><br/><strong>Effort estimate<br/><br/></strong>Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br/><br/><strong>Compensation<br/><br/></strong>Up to <strong>$50/hr equivalent</strong>, depending on level and pace. Tasks are estimated at :20 hours each; you set your own schedule. </div>