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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
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 $40/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.
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