Machine Learning Scientist - AI Trainer

DataAnnotation; Burbank (CA); Remote; USD 124,000 - 207,000; Full time

Benefits offered by this job

Flexible, remote work

Project-based work

Job summary

DataAnnotation is where 1M+ experts train the world’s leading AI models. Flexible, remote, and always project-available.

As a Machine Learning Engineer you’ll stress-test how models reason about ML systems and shape how the field handles your work. You’ll write prompts, review AI output for errors, and craft correct solutions grounded in real practitioner experience.

DataAnnotation offers flexible, remote, and always project-available collaboration across a global network of contributors.

Qualifications

• Hands-on experience training, evaluating, or deploying models.
• Comfort with the modern ML stack and Python.
• Clear written English; explanations as training signal.
• No degree required; focus on what you can do.

Responsibilities

• Write prompts that probe model reasoning about ML systems.
• Review AI output for subtle errors like leaky evaluations.
• Write correct solutions grounded in real practitioner experience.

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.