Machine Learning Scientist - AI Trainer

DataAnnotation; Springfield (MO); Remoto; USD 124.000 - 207.000; Tempo pieno

Descrizione del lavoro

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems, including training dynamics, evaluation design, data pipelines, and deployment trade-offs. You’ll write prompts, review AI outputs for subtle errors, and draft correct, grounded solutions based on practical experience.

This role emphasizes clear written English and hands-on work with Python and the ML stack (PyTorch or JAX) in a remote, project-based setup.

Competenze

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

Mansioni

• Write prompts that probe model reasoning in ML systems.
• Review AI outputs for subtle errors and misconfigurations.
• Write correct, grounded solutions when models fall short.

Conoscenze

Python

ML engineering

Model evaluation

Written English

Formazione

No degree required

Strumenti

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.