ML Reasoning Engineer - Remote, Flexible Projects

DataAnnotation; Lehi (UT); Remote; USD 170,000 - 243,000; Full time

Benefits offered by this job

Remote work

Flexible schedule

Job summary

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems, focusing on training dynamics, evaluation design, data pipelines, and deployment trade-offs. You will write prompts, review AI outputs for subtle errors, and craft correct solutions based on real practitioner experience.

Remote-friendly role with flexible project availability. The position emphasizes hands-on ML work using Python with PyTorch or JAX, and clear written communication in

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

Model training

Model evaluation

Model deployment

Python

Tools

PyTorch

JAX

Job description

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems, focusing on training dynamics, evaluation design, data pipelines, and deployment trade-offs. You will write prompts, review AI outputs for subtle errors, and craft correct solutions based on real practitioner experience.

Remote-friendly role with flexible project availability. The position emphasizes hands-on ML work using Python with PyTorch or JAX, and clear written communication in