ML Systems Evaluator & Prompt Architect (Remote)

DataAnnotation; New York (NY); Remote; USD 170,000 - 243,000; Full time

Benefits offered by this job

Remote work

Flexible projects

Job summary

DataAnnotation is seeking a Machine Learning Engineer to stress-test model reasoning, data pipelines, and deployment trade-offs. You’ll craft prompts, review model outputs for subtle errors, and write correct solutions grounded in practitioner experience.

The role emphasizes hands-on work with Python and PyTorch or JAX, clear written English, and the ability to work remotely. Compensation is competitive, with opportunities to earn $150+ per hour depending on tasks and specialization.

Qualifications

• Hands-on experience training, evaluating, or deploying models professionally or in serious personal work.

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

ML engineering

Python

PyTorch

JAX

Prompt engineering

English writing

Tools

Python

PyTorch

JAX

Job description

DataAnnotation is seeking a Machine Learning Engineer to stress-test model reasoning, data pipelines, and deployment trade-offs. You’ll craft prompts, review model outputs for subtle errors, and write correct solutions grounded in practitioner experience.

The role emphasizes hands-on work with Python and PyTorch or JAX, clear written English, and the ability to work remotely. Compensation is competitive, with opportunities to earn $150+ per hour depending on tasks and specialization.