ML Systems QA Engineer - Remote & Flexible

DataAnnotation; Topeka (KS); Remote; USD 170,000 - 243,000; Full time

Benefits offered by this job

Flexible, remote, project-based

Job summary

DataAnnotation is seeking a Machine Learning Engineer to 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.

You’ll write prompts that probe model reasoning about training, evaluation, debugging, and productionizing ML systems; review AI output for subtle errors; and draft correct solutions grounded in real-world experience.

Qualifications

• 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.

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

Hands-on ML experience

Python

PyTorch

JAX

Clear English

Tools

Python tooling

Job description

DataAnnotation is seeking a Machine Learning Engineer to 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.

You’ll write prompts that probe model reasoning about training, evaluation, debugging, and productionizing ML systems; review AI output for subtle errors; and draft correct solutions grounded in real-world experience.