Senior ML Engineer Expert - Remote QA & Policy Reviewer

AI Trainer Jobs; United States; Remote; USD 105,000 - 143,000; Full time

Job summary

AI Trainer Jobs seeks a Machine Learning Engineer Expert for a remote review track that evaluates AI outputs across specialist operations workflows. Reviewers assess workflow correctness, policy adherence, and stakeholder fit, flag operational risk, and document the next steps so the modeling team can train on it.

AuraOne uses experienced operators to grade outputs with the rigor of a senior peer, focusing on workflow, policy, and unwritten rules that decide completion.

Qualifications

• Direct working experience in machine learning engineer specialist operations on real teams for Machine Learning Engineer Expert work.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that names the policy or workflow being applied.
• Strong attention to detail and the ability to flag when a prompt itself is the problem.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against current machine learning engineer specialist operations workflows, playbooks, and firm policy for Machine Learning Engineer Expert 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.

Skills

Operational review

Policy adherence

Workflow judgment

Stakeholder communication

Machine Learning Engineer operations

Job description

AI Trainer Jobs seeks a Machine Learning Engineer Expert for a remote review track that evaluates AI outputs across specialist operations workflows. Reviewers assess workflow correctness, policy adherence, and stakeholder fit, flag operational risk, and document the next steps so the modeling team can train on it.

AuraOne uses experienced operators to grade outputs with the rigor of a senior peer, focusing on workflow, policy, and unwritten rules that decide completion.