Machine Learning Scientist - AI Trainer

DataAnnotation; Houma (LA); Remote; USD 96,000 - 248,000; Part time

Job summary

DataAnnotation is seeking a Machine Learning Engineer to stress-test model reasoning on ML systems and craft authoritative answers reflecting practitioner experience. You’ll focus on prompts, evaluation, and robust problem-solving in a flexible, remote setting.

Contributors often work on diverse tasks with Python, PyTorch, or JAX, shaping practical ML tooling and deployment strategies for real-world models.

Qualifications

• Hands-on experience training, evaluating, or deploying models professionally or in serious personal projects.
• Comfort with the modern ML stack; Python and PyTorch or JAX are common.
• Clear written English: explanations are the training signal.

Responsibilities

• 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.

Skills

Prompt engineering

Model evaluation

Python

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.