Machine Learning Scientist - AI Trainer

DataAnnotation; Washington; Remoto; USD 170.000 - 243.000; Tempo pieno

Vantaggi offerti da questo lavoro

Flexible, remote, project-available

Descrizione del lavoro

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems, focusing on training dynamics, evaluation design, data pipelines, and deployment trade-offs. You will write prompts that probe model behavior and review outputs for subtle errors.

You’ll craft correct, actionable solutions based on real practitioner experience. This remote, project-based role offers compensation up to $150+/hr, with earnings scaling with task difficulty and specialization.

Competenze

• Hands-on experience training, evaluating, or deploying models professionally or in serious personal work.
• Proficient with Python and PyTorch or JAX.
• Excellent written English communication.

Mansioni

• 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, misdiagnosed training failures.
• Write the correct solution when the model falls short, grounded in real practitioner experience.

Conoscenze

Hands-on ML model development

Python & PyTorch or JAX

Clear written English

Formazione

No degree required

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.