🌎 AI Trainer (ML Engineering), Remote- Contract
About The Position
This fully remote contract role uses machine learning expertise to create challenging technical tasks, evaluate model-generated work, identify failures, and establish objective standards for correct solutions. It is intended for candidates who have already completed substantive AI-training work. The work includes creating realistic machine learning engineering tasks for advanced AI models; developing task instructions, reproducible environments, reference solutions, and evaluation criteria; evaluating model-generated code, experiments, analyses, and technical deliverables; and identifying issues such as data leakage, incorrect validation, unstable training, performance problems, or lack of reproducibility. Compensation is output-based, and experts are paid for tasks that meet project specifications and quality requirements. Task availability and completion time may vary.
Requirements
- Prior paid experience training, evaluating, benchmarking, or improving AI systems.
- Strong practical proficiency with Python.
- Hands-on experience using PyTorch, JAX, TensorFlow, scikit-learn, XGBoost, LightGBM, or comparable machine learning tools.
- Provide public proof of skill, such as GitHub repositories or public model implementations, competition results, Hugging Face models or datasets, research publications or technical reports, open-source machine learning contributions, or public benchmarks, experiments, or technical projects.
Nice To Haves
- Experience creating AI-training tasks, reference answers, rubrics, graders, or benchmark problems.
- Experience reviewing other AI trainers’ technical submissions.
- Kaggle Expert, Master, or Grandmaster status, or strong results in another technical competition.
- Publications or open-source contributions in machine learning.
- Prior experience with long-horizon or agentic AI evaluations.
- Availability to begin immediately.
Responsibilities
- Create realistic machine learning engineering tasks that challenge advanced AI models.
- Develop task instructions, reproducible environments, reference solutions, and evaluation criteria.
- Evaluate model-generated code, experiments, analyses, and technical deliverables.
- Identify issues involving data leakage, incorrect validation, unstable training, performance, or reproducibility.
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What This Job Offers
Education Level
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