Machine Learning Scientist - AI Trainer

DataAnnotation; King of Prussia (PA); Remote; USD 170,000 - 243,000; Full time

Benefits offered by this job

Flexible remote work

Project-based work

Job summary

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems and to craft responsible, practical answers for real-world deployment. You’ll engage with prompts, review outputs for errors, and write the correct solution based on hands-on practitioner experience.

The role emphasizes Python and PyTorch or JAX, clear English communication, and the ability to work remotely on diverse tasks with flexible project scope.

Qualifications

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

Responsibilities

• Write prompts that probe model reasoning about ML systems.
• Review AI output for subtle errors and misdiagnoses.
• Write the correct solution when the model falls short, grounded in practice.

Skills

Python

PyTorch

JAX

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.