Machine Learning Scientist - AI Trainer

DataAnnotation; Cincinnati (OH); Remote; USD 124,000 - 207,000; Full time

Benefits offered by this job

Remote work

Flexible project-based work

Job summary

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about training dynamics, evaluation design, data pipelines, and deployment trade-offs. You’ll write prompts, review AI output for subtle errors, and craft correct solutions grounded in real practitioner experience.

This remote, contract-friendly role values hands-on ML work; Python and PyTorch or JAX are assumed. Compensation ranges up to 150+ USD per hour, with many contributors earning 100k–200k+ annually

Qualifications

• Hands-on experience training, evaluating, or deploying models.
• Comfort with Python stack (PyTorch/JAX).
• Excellent written English required; no degree required.

Responsibilities

• Write prompts that probe model reasoning about training, evaluation, and deployment.
• Review AI outputs for subtle errors such as leaky evaluations or wrong losses.
• Draft correct solutions grounded in practitioner experience.

Skills

ML experience

Python

PyTorch/JAX

English writing

Tools

PyTorch

JAX

Job description

Models are surprisingly bad at reasoning about themselves: training dynamics, evaluation design, data pipelines, and deployment trade-offs. Plausible-sounding ML advice is often subtly wrong.

As a Machine Learning Engineer you'll stress-test how models reason about ML systems and write the answers a strong practitioner would give, shaping how the next generation handles your field.

What you’ll actually do

• Write prompts that probe how models reason about training, evaluation, debugging, and productionizing ML systems.
• Review AI output for subtle errors: leaky evaluations, wrong loss formulations, and misdiagnosed training failures.
• Write the correct solution when the model falls short, grounded in real practitioner experience.

What we look for

• Hands-on experience training, evaluating, or deploying models professionally or in serious personal work.
• Comfort with the modern ML stack; most tasks assume Python and PyTorch or JAX.
• Clear written English: your explanations are the training signal.
• No degree required. We care about what you can do, not where you learned it.

Compensation

Up to $150+/hr depending on task difficulty and specialization. Many contributors add $100k–$200k a year; some make it their full-time income.

About DataAnnotation

DataAnnotation is where 1M+ experts train the world’s leading AI models. Hundreds of millions paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.