AI TRAINER (ML ENGINEERING) - REMOTE
Location: Global, Fully Remote
- Employment Type: Contractor
- Time Commitment: 15+ hours per week
- Schedule: Flexible
- Compensation: $60–$120/hour equivalent, paid per accepted task
ABOUT THE ROLE
We are seeking Machine Learning Engineers with prior professional AI-training or model-evaluation experience to support a project focused on improving advanced AI systems.
You will apply your machine learning expertise to develop challenging technical tasks, evaluate model-generated work, identify failures, and establish objective standards for correct solutions. This role is suited to candidates with substantive hands-on AI-training experience.
KEY 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, and reproducibility.
REQUIRED QUALIFICATIONS
Prior paid experience training, evaluating, benchmarking, or improving AI systems.
Strong practical proficiency in Python.
Hands-on experience with PyTorch, JAX, TensorFlow, scikit-learn, XGBoost, LightGBM, or comparable machine learning tools.
PUBLIC PROOF OF SKILL
Applicants should provide verifiable evidence of their expertise, such as:
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GitHub repositories or public model implementations.
Kaggle, DrivenData, AIcrowd, or similar competition results.
Hugging Face models or datasets.
Research publications or technical reports.
Open-source machine learning contributions.
Public benchmarks, experiments, or technical projects.
PREFERRED QUALIFICATIONS
Experience creating AI-training tasks, reference answers, rubrics, graders, or benchmark problems.
Experience reviewing technical submissions from other AI trainers.
Kaggle Expert, Master, or Grandmaster status, or strong results in other technical competitions.
Machine learning publications or open-source contributions.
Experience with long-horizon or agentic AI evaluations.
Availability to begin immediately.
APPLICATION PROCESS
Submit your application, AI-training experience, and public technical evidence.
Complete an AI interview covering technical and integrity checks.
Undergo a hiring-manager review.
Complete project onboarding and begin your first assigned task if selected.
COMPENSATION AND WORK ARRANGEMENT
Compensation is output-based, with an estimated equivalent of $60–$120 per hour. Payment is made for tasks that meet project specifications and quality requirements. Task availability and completion time may vary.
This is a global, fully remote contractor opportunity with a flexible schedule and a minimum commitment of 15 hours per week.
