Machine Learning Engineer Expert

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

Machine Learning Engineer Expert is a remote review track for evaluating AI outputs across machine learning engineer specialist operations workflows. Reviewers grade workflow correctness, policy adherence, and stakeholder fit; flag operational risk; and document the right next step so the modeling team can train on it.

Category: Education & Learning Evaluation · Pay: $90 / hr · Location: Remote — US-eligible · Contractor

Machine Learning Engineer Expert is a remote review track for evaluating AI outputs across machine learning engineer specialist operations workflows.

Role details

About the role

Machine Learning Engineer Expert is a remote review track for evaluating AI outputs across machine learning engineer specialist operations workflows. Reviewers grade workflow correctness, policy adherence, and stakeholder fit; flag operational risk; and document the right next step so the modeling team can train on it.
Machine Learning Engineer specialist operations AI has to fit into an actual day at work. AuraOne uses experienced operators to grade outputs the way a senior peer would — checking workflow, policy, and the unwritten rules that decide whether a task actually gets done.
Review tutoring and assessment output. Judge it against how real learners use it.

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.

What you should bring

• 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.

Example tasks

• Grade a model's response to a real machine learning engineer specialist operations ticket and rate workflow, tone, and escalation.
• Flag a missed escalation with the right severity tag and corrected next step.
• Adjudicate a disputed playbook call between two reviewers using firm guidance.
• Audit a 25-row batch for rubric consistency and report drift to the program lead.

Useful experience

• Prior experience training, calibrating, or QA-ing operations teams.
• Familiarity with AI-assisted workflow tooling and its failure modes.
• Bilingual experience for cross-region operations.

Compensation and schedule

$90 / hr
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Operational review
• Policy adherence
• Workflow judgment
• Stakeholder communication
• Machine Learning Engineer specialist operations