Headquarters: Canada
URL: https://mindrift.ai/
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.
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:
What this is NOT
What we look for
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.
How it works
Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid
Effort estimate
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.
Compensation
Up to $50/hr equivalent, depending on level and pace. Tasks are estimated at ~20 hours each; you set your own schedule.
To apply: https://weworkremotely.com/remote-jobs/mindrift-senior-software-engineer-ai-agent-evaluation
Mindrift, powered by Toloka, is a platform that connects domain specialists and experts with AI project opportunities from major tech innovators. The company focuses on post-training and evaluation of frontier AI models by creating domain-specific reinforcement learning environments, tasks, and evaluation frameworks. Mindrift enables experts across fields—including mobile development, management consulting, physics research, and other domains—to shape how next-generation generative models learn and perform by converting real-world expertise into structured learning environments. The platform operates on a project-based model, allowing contributors to work on diverse AI initiatives including mobile app development, consulting domain training, physics problem design, and other specialized tasks for leading technology companies.
