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Engagement Type: Independent Contractor
Work Mode: Remote
Schedule: (15–25 hrs/week, flexible up to 40 hrs)
Duration: 1–3 Months | Immediate
Location: Geography restricted to the USA, UK, Canada, EU
Type: Full-time or Part-time Contract Work
Fluent Language Skills Required: English
Role
Partners with leading AI teams to improve the quality, usefulness, and reliability of general-purpose conversational AI systems. These systems are used across a wide range of everyday and professional scenarios, and their effectiveness depends on how clearly, accurately, and helpfully they respond to real user questions.
In mathematics-related contexts, conversational AI systems must demonstrate precise formal reasoning, mathematical rigor, and conceptual clarity. This project focuses on evaluating and improving how models reason about mathematical problems, explanations, and proofs across both foundational and advanced areas of mathematics.
What You’ll Do
Write and refine prompts to guide model behavior in mathematical contexts
Evaluate LLM-generated responses to mathematics-related queries for correctness, rigor, and logical coherence
Verify mathematical claims, derivations, and proofs using domain expertise
Conduct fact-checking using authoritative public sources and domain knowledge
Annotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuracies
Assess clarity, structure, and appropriateness of explanations for different audiences
Ensure model responses align with expected conversational behavior and system guidelines
Apply consistent evaluation standards by following clear taxonomies, benchmarks, and detailed evaluation guidelines
Who You Are
You hold a PhD in Mathematics or a closely related field
You have demonstrated experience in Probability & Statistics, and may also have experience in one or more of the following areas:
Algebra & Number Theory
Calculus & Analysis
Geometry & Topology
Discrete Mathematics, Logic & Computation
You have significant experience using large language models (LLMs) and understand how and why people use them
You have excellent writing skills and can clearly explain complex mathematical concepts
You have strong attention to detail and consistently notice subtle issues others may overlook
Experience reviewing or editing technical or academic writing
Nice-to-Have Specialties
Prior experience with RLHF, model evaluation, or data annotation work
Experience teaching, mentoring, or explaining mathematical concepts to non-expert audiences
Familiarity with evaluation rubrics, benchmarks, or structured review frameworks
What Success Looks Like
You identify inaccuracies or weak reasoning in mathematical-related model outputs
Your feedback improves the rigor, clarity, and correctness of AI explanations
You deliver consistent, reproducible evaluation artifacts that strengthen model performance
Customers trust their AI systems in mathematical contexts because you’ve rigorously evaluated them
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