ML Systems Auditor & AI Reasoning Trainer — Remote

DataAnnotation; Arizona; Remote; USD 170,000 - 243,000; Full time

Benefits offered by this job

Remote-friendly

Flexible projects

Competitive hourly pay

Job summary

DataAnnotation seeks a Machine Learning Engineer to stress-test model reasoning about ML systems, including training, evaluation, debugging, and productionizing workflows. You will craft prompts and review outputs to uncover subtle issues and then provide correct solutions grounded in hands-on practitioner experience.

The role emphasizes Python and modern ML stacks (PyTorch or JAX), remote-friendly work, and a performance-based compensation model that can reach $150+ per hour depending on task

Qualifications

• Hands-on experience training, evaluating, or deploying models.
• Proficient Python, PyTorch or JAX.
• Clear written English; no degree required.

Responsibilities

• Write prompts that probe how models reason about training, evaluation and productionizing ML systems.
• Review AI output for subtle errors and misdiagnosed training failures.
• Write correct solutions grounded in real practitioner experience.

Skills

Python

PyTorch

JAX

Job description

DataAnnotation seeks a Machine Learning Engineer to stress-test model reasoning about ML systems, including training, evaluation, debugging, and productionizing workflows. You will craft prompts and review outputs to uncover subtle issues and then provide correct solutions grounded in hands-on practitioner experience.

The role emphasizes Python and modern ML stacks (PyTorch or JAX), remote-friendly work, and a performance-based compensation model that can reach $150+ per hour depending on task