Mindrift

Freelance Agent Evaluation Engineer

Mindrift
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20 hours ago
Remote, United Kingdom +4 moreSenior

Responsibilities

  • Build realistic simulated developer environments with codebases, infrastructure, tickets, documentation, and conversations.
  • Design challenging coding tasks from intermediate environment states and define solvability and acceptance criteria.
  • Write functional and integration tests that fairly evaluate AI agent solutions.
  • 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 and FastAPI, JavaScript or TypeScript and React, Docker, Postgres, Kafka, and Redis.
  • Experience writing functional and integration tests.
  • B2 or higher English proficiency.
  • A master’s degree in computer science, software engineering, data science/data analytics, artificial intelligence/machine learning, computational linguistics/natural language processing, information systems, or a related field; a bachelor’s degree is accepted with five years of experience.
  • At least 3 years of professional experience in related QA-automation/testing or cybersecurity roles is stated for those domains.

Benefits

  • Part-time, remote, project-based freelance work that can fit around primary professional or academic commitments.
  • Work on advanced AI projects and build portfolio experience influencing future AI systems.
  • Paid per accepted task, with an effective rate of up to $50 per hour depending on qualification tier and task efficiency.
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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