Open Source Contributor for Technical AI Training

You will create and assess difficult tasks based on real software, scientific, hardware, and engineering work. The tasks help measure whether AI systems can reason, write code, use technical tools, and complete longer projects.

You will combine hands-on programming with careful technical review. Your work must be reproducible, meaning another person should be able to run it and reach the same result.

• Create realistic technical tasks based on professional, scientific, or engineering workflows.
• Build reproducible environments, reference solutions, tests, and clear evaluation criteria.
• Review AI-generated work for correctness, completeness, reproducibility, and technical quality.
• Find model failures and explain why an approach or result is incorrect.
• Work across software engineering, machine learning, scientific computing, hardware, embedded systems, electronics, infrastructure, automation, and security.

What it pays and takes

This is flexible, fully remote contractor work. Compensation is output-based and paid for accepted tasks that meet the project specifications and quality requirements.

• $60 to $120 per hour equivalent, paid per task that meets the project specifications.
• Part-time work with a commitment of less than 20 hours per week.
• Open to candidates in the listed countries.
• Professional fluency in English.
• Strong programming ability and practical proficiency in Python.
• Meaningful merged contributions to established open-source repositories or substantial original public projects.
• Demonstrable work involving implementation, debugging, testing, performance, infrastructure, simulation, or data processing.
• Expertise in at least one relevant software, science, hardware, or engineering field.
• Public evidence of technical work, such as maintainer responsibilities, technical tools, scientific software, research code, or substantial repositories.
• Careful judgment when assessing correctness, completeness, reproducibility, and quality.

Helpful background

Experience designing technical tests, benchmarks, evaluation tasks, or reproducible environments is useful. Code review experience, publications, competition results, public technical writing, or long-term work on complex projects can also show relevant expertise.

Previous AI-training experience is not required.

How it works

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

The hiring platform's application for this job asks for your resume, your LinkedIn profile, your phone number, your location and answers to 8 screening questions.

About AI training work

AI training is the human work behind systems that write, code, reason, and use tools. Experienced contributors are paid to create reliable examples, test difficult cases, and judge whether model outputs are correct and useful.