Subject Matter Experts: ML Model Evaluation
Weekday AI
Subject Matter Experts: ML Model Evaluation
Weekday AI
Proactive software engineer recruitment via referrals
Weekday AI · United States (Remote) · Full-time · Posted 2026-11-13
Workplace: remote
Department: AI Training
This role is for one of Weekday’s clients
Engagement Type: Independent Contractor
Work Arrangement: Fully Remote
Estimated Commitment: Approximately 5 Hours
Schedule: Flexible, Asynchronous
Payment Frequency: Weekly, based on services rendered
Eligibility:
Note:
We are seeking highly qualified Subject Matter Experts with PhD-level academic or professional expertise across specialised research and professional domains to participate in a paid Machine Learning (ML) Model Evaluation project.
The project focuses on assessing the quality, accuracy, and reliability of AI-generated responses to complex research prompts and domain-specific questions. Your evaluations will help identify where current machine learning models perform effectively and where their outputs require further refinement.
This opportunity is suited to experienced researchers, academics, data analysts, technical writers, and domain specialists who can critically assess complex information, identify factual inaccuracies, and provide structured, evidence-based feedback.
Professionals from the following backgrounds are encouraged to apply:
During the interview process, candidates may be assessed on their review practices, critical thinking, and ability to improve the quality of their evaluations. Responses should address the following three habits:
The ideal candidate combines deep subject matter expertise with strong research judgement and analytical precision. They should be comfortable reviewing complex AI-generated content, distinguishing accurate information from flawed reasoning, and communicating their assessments through clear, structured feedback.
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Proactive software engineer recruitment via referrals
Weekday.works helps companies hire software engineers through proactive outreach and peer-recommended candidates. Its platform automates tracking, pipeline management, and provides weekly updates, while it actively identifies engineers via peer networks, reaches out, shortlists, checks references, and schedules interviews. Differentiators include peer-backed vetting instead of traditional job boards, proactive outreach, and a passive-income reference feature that monetizes referrals. The goal is to reduce the time and effort of hiring by connecting companies with pre-vetted engineers who are open to new opportunities through a network-driven approach.
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