Machine Learning Scientist - AI Trainer

DataAnnotation; Boston (MA); Remoto; USD 83.000 - 207.000; Tempo pieno

Descrizione del lavoro

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems, covering training dynamics, evaluation design, data pipelines, and deployment choices.

You'll write prompts, review AI outputs for subtle errors, and craft correct, grounded solutions based on real practitioner experience. This role embraces hands-on model work and clear written communication. Remote-friendly guidance and project-based collaboration are available.

Competenze

• Hands-on experience training, evaluating, or deploying models.
• Proficiency with Python and PyTorch or JAX.

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

Conoscenze

Hands-on ML experience

Clear written English

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.