Remote ML Systems Engineer: Probe & Improve Reasoning

DataAnnotation; Chandler (AZ); Remote; USD 83,000 - 207,000; Full time

Benefits offered by this job

Remote work

Job summary

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems and to craft practical answers for the next generation of practitioners. You’ll write prompts that probe training, evaluation, debugging, and productionizing ML workflows, review AI output for subtle errors, and write the correct solution when the model falls short—grounded in real-world experience.

The role offers remote-friendly, flexible work with competitive compensation up to $150+ per

Qualifications

• Hands-on experience training, evaluating, or deploying models professionally or in serious personal work.
• Comfort with 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.

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

Skills

Model training

Model evaluation

Model deployment

Python

PyTorch

JAX

Tools

PyTorch

JAX

Job description

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems and to craft practical answers for the next generation of practitioners. You’ll write prompts that probe training, evaluation, debugging, and productionizing ML workflows, review AI output for subtle errors, and write the correct solution when the model falls short—grounded in real-world experience.

The role offers remote-friendly, flexible work with competitive compensation up to $150+ per