AI Trainer (ML Engineering)

Micro1; India; Remote; INR 7,768,000 - 15,537,000; Part time

Job summary

Cashback24x7 is seeking Machine Learning Engineers with hands-on AI training or model-evaluation experience to support a project focused on advancing AI systems. You will create realistic tasks, set evaluation standards, and examine model outputs to improve reliability.

The role is fully remote, contract-based, offering flexible hours and a pay-per-task structure. Availability to begin immediately is preferred.

Qualifications

• Prior paid experience training, evaluating, benchmarking, or improving AI systems.
• Strong practical proficiency with Python.
• Hands-on experience using ML frameworks (PyTorch, JAX, TensorFlow, scikit-learn, XGBoost, LightGBM).

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.

Skills

Python

PyTorch

TensorFlow

scikit-learn

XGBoost

LightGBM

ML evaluation

AI training

Tools

GitHub

Kaggle

Hugging Face

Job description

Job DescriptionPay: $60–$120/hour equivalent, paid per accepted taskLocation: Global, fully remoteJob Type: ContractorTime Commitment: 15+ hours per weekSchedule: 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 SkillStrong 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.

Compensation

CompensationCompensation is output-based. Experts are paid for tasks that meet project specifications and quality requirements. Task availability and completion time may vary.