ML Engineer: Prompted Reasoning & Evaluation (Remote)

DataAnnotation; Virginia; Remote; USD 170,000 - 243,000; Full time

Benefits offered by this job

Flexible, remote work

Project-based availability

Job summary

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems, training dynamics, evaluation design, data pipelines, and deployment trade-offs. You will write prompts that probe model reasoning, review AI output for subtle errors, and craft correct solutions grounded in practical experience.

Join a flexible, remote, project-based environment where no degree is required and compensation reflects task complexity.

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

Python

PyTorch

JAX

Strong written English

Remote work experience

Tools

PyTorch

JAX

Python

Job description

DataAnnotation is seeking a Machine Learning Engineer to stress-test how models reason about ML systems, training dynamics, evaluation design, data pipelines, and deployment trade-offs. You will write prompts that probe model reasoning, review AI output for subtle errors, and craft correct solutions grounded in practical experience.

Join a flexible, remote, project-based environment where no degree is required and compensation reflects task complexity.