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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.
What this opportunity involves
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 virtual companies following a high-level plan - codebase, infrastructure, and context (conversations, documentation, tickets) that form a realistic environment with development history
- Assemble and calibrate tasks from intermediate states of the virtual company: craft the prompt, define evaluation criteria, and ensure the task is solvable and the evaluation is fair
- Design tasks set in isolated environments - emulations of a developer's workstation: a Linux machine with development tools (terminal, CLI), MCP servers (repository, task tracker, messenger, documentation, etc.), and a real web application codebase
- Write tests that accept all correct solutions and reject incorrect ones - neither too strict (breaking on valid approaches) nor too lenient (passing bad ones)
- Iterate with an AI agent on tests - verifying they catch real problems, don't miss bad solutions, and don't break on good ones
- Review code written by agents, analyze why an agent failed or succeeded, and design edge cases and adversarial scenarios
- Iterate based on feedback from expert QA reviewers who score your work on quality criteria
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
A significant part of the work is done together with AI - it's very hard to create tasks that challenge frontier models without using frontier models.
What we look for
This opportunity is a good fit for experienced developers, software engineers, and/or test automation specialists open to part-time, non-permanent projects. Ideally, contributors will have:
- Degree in Computer Science, Software Engineering, or related fields
- 5+ years in software development, primarily Python (FastAPI, pytest, async/await, subprocess, file operations)
- Background in full-stack development, with experience building React-based interfaces (JavaScript/TypeScript) and robust back-end systems
- Experience writing tests (functional, integration — not just running them)
- Docker containers, and familiarity with infrastructure tools (Postgres, Kafka, Redis)
- CI/CD understanding (GitHub Actions as a user: triggers, labels, reading results)
- English proficiency - B2