Remote ML Systems Engineer - Prompting and Evaluation

DataAnnotation; Arden Hills (MN); Remote; USD 170,000 - 243,000; Part time

Job summary

DataAnnotation is hiring a Machine Learning Engineer to stress-test model reasoning about ML systems, evaluation design, data pipelines, and deployment trade-offs. You’ll write prompts and review AI outputs, then craft correct solutions grounded in real practitioner experience.

You should have hands-on experience training, evaluating, or deploying models, be comfortable with Python and libraries like PyTorch or JAX, and communicate clearly in written English. No degree is required.

Qualifications

• Hands-on experience training, evaluating, or deploying models professionally or in serious personal work.
• Comfort with the modern ML stack; Python and PyTorch or JAX.
• Clear written English: your explanations are the training signal.
• No degree required.

Responsibilities

• Write prompts to 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.

Tools

Python

PyTorch

JAX

Job description

DataAnnotation is hiring a Machine Learning Engineer to stress-test model reasoning about ML systems, evaluation design, data pipelines, and deployment trade-offs. You’ll write prompts and review AI outputs, then craft correct solutions grounded in real practitioner experience.

You should have hands-on experience training, evaluating, or deploying models, be comfortable with Python and libraries like PyTorch or JAX, and communicate clearly in written English. No degree is required.