AI Trainer (ML Engineering)

The role

Pay: $60–$120/hour equivalent, paid per accepted task Location: Global, fully remote Job Type: Contractor Time Commitment: 15+ hours per week Schedule: Flexible micro1 is looking for Machine Learning Engineers with prior professional AI-training or model-evaluation experience to support a project focused on improving advanced AI systems. You will use your machine learning expertise to create challenging technical tasks, evaluate model-generated work, identify failures, and establish objective 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 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. Required Qualifications • 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 ML tools. Public Proof of Skill Strong applicants should provide evidence such as: • 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 ML contributions • Public benchmarks, experiments, or technical projects Preferred Qualifications • 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. Application Process • Submit your application, AI-training experience, and public technical evidence. • Complete an AI interview containing technical and integrity checks. • Complete a hiring-manager review. • If selected, complete project onboarding and begin your first assigned task. Compensation • Compensation is output-based. Experts are paid for tasks that meet project specifications and quality requirements. Task availability and completion time may vary. Originally posted on Himalayas