Remote ML Evaluation Researcher (Contractor) — Policy & QA

AuraOne, Inc.; United States; Remote; USD 55,000 - 110,000; Full time

Job summary

AuraOne, Inc. is seeking a Machine Learning Researcher to remotely evaluate AI outputs within specialist operations workflows. You will review, judge, and document outcomes to guide model training and policy adherence.

The role requires MSc or PhD and reliable async availability of at least 10 hours per week, with experience applying structured rubrics and clear written reasoning about policies and workflows.

Qualifications

• Direct experience in ML researcher operations on real teams.
• Comfort applying multi-page rubrics across long batches.
• Clear written reasoning naming the policy or workflow applied.
• Strong attention to detail and ability to flag when a prompt is the problem.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against workflows, playbooks, and firm policy for ML Researcher — Remote AI Evaluation assignments.
• Grade tone, escalation logic, and stakeholder fit on a structured rubric.
• Flag operational risk, missed escalations, and policy-adherence gaps with severity tags.
• Capture the right next step so the modeling team can train on it.
• Adjudicate disputed treatments against published playbooks or firm guidance.
• Maintain reviewer-quality scores in inter-rater calibration cycles.

Skills

Operational review

Policy adherence

Workflow judgment

Stakeholder communication

Machine Learning Researcher specialist

AI model evaluation

Education

MSc or PhD in a relevant field

Job description

AuraOne, Inc. is seeking a Machine Learning Researcher to remotely evaluate AI outputs within specialist operations workflows. You will review, judge, and document outcomes to guide model training and policy adherence.

The role requires MSc or PhD and reliable async availability of at least 10 hours per week, with experience applying structured rubrics and clear written reasoning about policies and workflows.