ML Systems Scientist — Remote, Flexible Projects

DataAnnotation; Lawrence (KS); Remote; USD 170,000 - 243,000; Full time

Benefits offered by this job

Flexible schedule

Remote work

Project-based, constant opportunities

Job summary

DataAnnotation is seeking an experienced Machine Learning Engineer to stress-test model reasoning about training dynamics and deployment trade-offs. You will craft prompts, review model outputs for subtle errors, and write corrected, practitioner-grounded solutions.

You’ll operate in a flexible, remote setup with exposure to Python and PyTorch or JAX, collaborating with a broad contributor network. No formal degree is required; your hands-on ability matters most.

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

ML model training

Model evaluation

Deployment experience

Python

PyTorch/JAX

Tools

Python

PyTorch

JAX

Job description

DataAnnotation is seeking an experienced Machine Learning Engineer to stress-test model reasoning about training dynamics and deployment trade-offs. You will craft prompts, review model outputs for subtle errors, and write corrected, practitioner-grounded solutions.

You’ll operate in a flexible, remote setup with exposure to Python and PyTorch or JAX, collaborating with a broad contributor network. No formal degree is required; your hands-on ability matters most.