AI Trainer (SWE)

Overview

micro1 is hiring software engineers with prior paid AI-training or model-evaluation experience for a fully remote contractor project focused on improving advanced AI systems. The work is task-based and output-based, with compensation tied to accepted tasks that meet project requirements and quality standards.

Selected contributors will use software engineering expertise to design challenging technical tasks, evaluate model-generated code, and define clear standards for correct solutions. This role is intended for candidates who have already completed substantive AI-training work.

What You'll Work On

• Create realistic software engineering tasks that challenge advanced AI models.
• Develop task instructions, reproducible environments, reference solutions, tests, and evaluation criteria.
• Review model-generated code and technical deliverables for correctness, robustness, and completeness.
• Identify issues related to implementation, debugging, dependencies, performance, testing, and reproducibility.

Requirements

• Prior paid experience training, evaluating, benchmarking, or improving AI systems.
• Strong practical proficiency with Python.
• Professional experience with at least one additional programming language, such as Java, JavaScript, TypeScript, Rust, C++, C#, or Go.
• Strong knowledge of software design, debugging, testing, version control, and dependency management.
• Applicants should be able to provide public evidence of skill, such as substantial GitHub or GitLab repositories, meaningful open-source contributions, maintainer or core-contributor responsibilities, programming competition results, public developer tools or technical projects, or technical publications/benchmarks/write-ups.

Preferred Qualifications

• Experience creating AI-training tasks, reference solutions, tests, graders, or benchmark problems.
• Experience reviewing other AI trainers’ technical submissions.
• Codeforces rating of approximately 1900 or higher, or similarly strong programming-competition results.
• Experience with Linux, Docker, CI/CD, command-line tools, or sandboxed environments.
• Prior experience with long-horizon or agentic coding evaluations.
• Availability to begin immediately.

Application Process

1. Submit your application, AI-training experience, and public technical evidence.
2. Complete an AI interview with technical and integrity checks.
3. Complete a hiring-manager review.
4. If selected, complete project onboarding and begin assigned work.

Compensation

Compensation is output-based, with experts paid for tasks that meet project specifications and quality requirements. Task availability and completion time may vary.