ML Systems Prompt Engineer - Remote & Flexible

DataAnnotation; Logan (UT); Remote; USD 165,000 - 248,000; Full time

Job summary

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems and to write answers a strong practitioner would give, shaping how the next generation handles your field.

You’ll write prompts that probe training, evaluation, debugging, and productionizing ML systems, review AI output for subtle errors, and provide correct solutions grounded in real-world practitioner experience. Remote-friendly, project-based work.

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

Model deployment

Model evaluation

Tools

Python

PyTorch

JAX

Job description

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems and to write answers a strong practitioner would give, shaping how the next generation handles your field.

You’ll write prompts that probe training, evaluation, debugging, and productionizing ML systems, review AI output for subtle errors, and provide correct solutions grounded in real-world practitioner experience. Remote-friendly, project-based work.