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 historyDesign tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agentWrite tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenientIterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robustWhat this is NOT:Not data labelingNot prompt engineeringNot writing code from scratch - the agent writes most of the code; you guide and evaluateWhat we look for:5+ years in software developmentCore stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, RedisExperience 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 benefitsEducational qualificationsA 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 ExperienceCandidates should have a minimum of 3 years of professional experience in related roles or domain - specifically for QA-automation/testing or cybersecurity rolesHow it worksApply → Pass qualification(s) → Join a project → Complete tasks → Get paidCompensation: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.
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.
