Mindrift

Freelance Agent Evaluation Engineer

Mindrift
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20 hours ago
Remote, Germany +5 moreSenior

Responsibilities

  • Build realistic simulated developer environments containing codebases, infrastructure, tickets, documentation, and conversations.
  • Design challenging tasks from intermediate environment states, including prompts and definitions of success.
  • Write functional and integration tests that accept valid solutions and reject incorrect ones.
  • Review agent solutions, analyze failures, and iterate on tasks and tests based on QA feedback.

Requirements

  • At least 5 years of software development experience.
  • Experience with Python, FastAPI, JavaScript/TypeScript, React, Docker, Postgres, Kafka, and Redis.
  • Experience writing functional and integration tests.
  • Master’s degree in a relevant field, or a bachelor’s degree with five years of experience.
  • At least 3 years of professional experience in related roles or domains, specifically for QA-automation/testing or cybersecurity roles.
  • English proficiency at B2 level or higher.
  • CV submitted in English with English proficiency indicated.

Benefits

  • Part-time, remote, freelance project-based work that can fit around other professional or academic commitments.
  • Opportunity to work on advanced AI projects and enhance a professional portfolio.
  • Opportunity to influence how future AI models understand and communicate in the field.
  • Payment per accepted task, with an effective rate of up to the equivalent of $50/hr.
  • Participation is project-based and not permanent employment.
Mindrift

About Mindrift

1,001-5,000 employees

Mindrift builds an expert-sourcing platform that connects domain specialists to project-based work training and evaluating generative AI models, including supervised fine-tuning, RLHF, evaluation, and red-teaming. It is built and operated by Toloka, part of Nebius Group, and run from Amsterdam, Netherlands. Work is fully remote and freelance, serving global technology companies developing and improving large AI systems.

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