Up to US$40
🇬🇧Freelance Agent Evaluation Engineer
Spain·Part-time·Added 3 days ago
50 open roles
What they offer
Up to US$40 an hour
Gross, as stated in the ad.
Part-time hours
Per the ad.
Fully remote
Per the ad.
What they ask for
Have the right to work in Spain
Mindrift doesn't mention sponsorship in the ad.
Work in English
English is required, per the ad.
Have 3+ years of experience
Mid-level role.
About the job
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.
What you'll do
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 we're looking 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.
Candidates should have a minimum of 3 years of professional experience in related roles or domain - specifically for QA-automation/testing or cybersecurity roles
Education & certifications
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
Languages
Please submit your CV in English and indicate your level of English proficiency.
What you'll get
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 $40/hr. Because payment is per task, a faster pace raises your effective hourly rate.
How you'll work
- 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.
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
How they hire
Submitting your CV
Completing assessments or interviews
In your own time
Language assessments, skills tests or an automated AI-led interview, alone or combined, done on your own schedule.
Verifying your identity · In your own time · 1–5 days
Joining a project and onboarding
In your own time
Review project guidelines and join the project Discord, or wait in a talent pool until a project opens.
- Identity verification through Persona usually takes a few days.
- The wait for a project varies: active projects onboard quickly, talent-pool placements can be delayed.
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