Remote Math; PhD - AI Trainer

Location:

Geography restricted to USA, UK, Canada, EU

Type:
Full-time or Part-time Contract Work

Fluent Language

Skills Required:

English

Mercor 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.

• 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

• 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

• 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

• 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
• Mercor customers trust their AI systems in mathematical contexts because you’ve rigorously evaluated them

Mercor provides mathematicians with the opportunity to apply deep theoretical expertise to the evaluation and improvement of advanced AI systems. This flexible, remote role allows you to influence how mathematical reasoning is represented and communicated at scale.