ML Systems Reasoning Engineer — Remote & Flexible

DataAnnotation; South Dakota; Remote; USD 124,000 - 207,000; 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 will write prompts, review AI output for subtle errors, and craft correct solutions grounded in practitioner experience. This is a flexible, remote role in the United States with strong English and Python/PyTorch/JAX skills.

Qualifications

• Hands-on experience training, evaluating, or deploying models professionally or in serious personal work.
• Comfort with Python and PyTorch or JAX in the modern ML stack.
• Clear written English; your explanations are the training signal.
• No degree required; focus on what you can do, not where you learned it.

Responsibilities

• Write prompts that probe model reasoning about training, evaluation, debugging, and productionizing ML systems.
• Review AI output for subtle errors: leaky evaluations, wrong loss formulations, misdiagnosed training failures.
• Write the correct solution when the model falls short, grounded in real practitioner experience.

Skills

Hands-on ML

Python

PyTorch/JAX

Clear written English

No degree required

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 will write prompts, review AI output for subtle errors, and craft correct solutions grounded in practitioner experience. This is a flexible, remote role in the United States with strong English and Python/PyTorch/JAX skills.