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About the Role The company 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. Responsibilities - 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. Requirements - 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. 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 the 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. 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. Benefits - 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.
