AI Systems Engineer
Company: Hire Feed
Location: Location not specified (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-06-19
About this role
- Role
: Talent Acquisition Manager
- Location
: Remote (Work from Anywhere)
- Payout
: $80–120 per hour
Role Overview:
We are hiring for one of our clients, seeking a People ops / recruiting Evaluator to work on a contractual basis. This role involves reviewing AI-generated work products—such as documents, spreadsheets, and slide decks—used in people operations and recruiting functions. The work requires evaluating accuracy, rigor, and domain-specific quality to ensure outputs meet professional standards.
Key Responsibilities:
• Evaluate AI-generated artifacts against domain-specific quality rubrics to assess accuracy and relevance.
• Identify factual errors, inconsistencies, and aesthetic flaws in documents, spreadsheets, and slide presentations.
• Grade outputs for rigor, clarity, and alignment with industry best practices in people operations and recruiting.
• Provide structured, written feedback that clearly articulates strengths and areas for improvement.
• Work remotely with flexibility to deliver timely, high-quality evaluations on a project basis.
Required Skills & Qualifications:
• Minimum of five years of professional experience in people operations, recruiting, or related human resources functions.
• Native or professional fluency in English with strong written communication skills.
• High proficiency in Microsoft Office and Google Workspace, with specific expertise in Google Slides and PowerPoint.
• Ability to assess technical and non-technical content with attention to detail and domain-specific standards.
• Experience working with evaluation frameworks or rubrics in professional or academic settings.
More About the Opportunity:
This role offers a unique opportunity to contribute to the development of AI-driven tools used in human resources and recruiting workflows at a global technology leader. Evaluators play a direct role in improving the reliability and effectiveness of AI outputs that support hirin...