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Mathematics Specialist

Job in Toronto, Ontario, M5A, Canada
Listing for: Great Value Hiring
Full Time position
Listed on 2026-02-23
Job specializations:
  • Education / Teaching
    Mathematics, Data Scientist
Salary/Wage Range or Industry Benchmark: 73.29 CAD Hourly CAD 73.29 HOUR
Job Description & How to Apply Below
Math (PhD) [$73.29/hr]
Math Experts to evaluate and improve how models reason about mathematical problems, explanations, and proofs across both foundational and advanced areas of mathematics.

Role Responsibilities

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

Good Candidature

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

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