Remote ML Systems Thinker: Prompt Engineer & Debugger

DataAnnotation; Palo Alto (CA); Remote; USD 170,000 - 243,000; Full time

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’ll write prompts and review AI outputs for subtle errors, then craft correct solutions grounded in real practitioner experience.

With a focus on practical impact and clear English explanations, this role offers flexible, remote work and compensation up to $150+ per hour, with many contributors

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 development

Model evaluation

Technical writing

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’ll write prompts and review AI outputs for subtle errors, then craft correct solutions grounded in real practitioner experience.

With a focus on practical impact and clear English explanations, this role offers flexible, remote work and compensation up to $150+ per hour, with many contributors