ML Engineer - AI Reasoning Trainer (Remote, Flexible)

DataAnnotation; Provo (UT); Remote; USD 170,000 - 243,000; Full time

Benefits offered by this job

Flexible, remote work

Project-based opportunities

Competitive hourly pay

Job summary

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 will write prompts that probe reasoning, review model outputs for subtle errors, and craft correct solutions grounded in real practitioner experience.

Comfort with Python and modern ML stacks (PyTorch or JAX) and clear written English are essential.

Qualifications

• Hands-on experience training, evaluating, or deploying models.
• Proficient in Python and ML frameworks (PyTorch or JAX).
• Clear written English; explanations are the training signal.
• No degree required; focus on what you can do, not where you learned it.

Responsibilities

• 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.

Skills

Hands-on ML experience

Python

PyTorch

JAX

Clear written English

No degree required

Tools

Python

PyTorch

JAX

Job description

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 will write prompts that probe reasoning, review model outputs for subtle errors, and craft correct solutions grounded in real practitioner experience.

Comfort with Python and modern ML stacks (PyTorch or JAX) and clear written English are essential.