Machine Learning Scientist - AI Trainer

DataAnnotation; Sandy Springs (GA); Remoto; USD 170.000 - 243.000; Tempo pieno

Descrizione del lavoro

DataAnnotation is seeking a Machine Learning Engineer to stress-test model reasoning about ML systems, including training dynamics, evaluation design, data pipelines, and deployment trade-offs. You will write prompts, review outputs, and craft correct solutions grounded in real practitioner experience.

Remote-friendly role with flexible project work. Compensation reflects hourly work and project variability, with emphasis on practical impact and measurable results.

Competenze

• Hands-on experience training, evaluating, or deploying models.
• Clear written English: your explanations are the training signal.
• Comfort with the modern ML stack; Python and PyTorch or JAX.
• No degree required; focus on ability over formal credentials.

Mansioni

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

Conoscenze

Hands-on ML deployment

Python/PyTorch/JAX

Clear written English

No degree required

Strumenti

Python

PyTorch

JAX

Descrizione del lavoro

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.