Math Expert
Keystone Recruitment
Job Overview
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Job Description
Math Expert at Keystone Recruitment
One of our clients, a leading AI research organization, is working to improve the quality, usefulness, and reliability of general-purpose conversational AI systems. These systems are used across a wide range of professional and everyday contexts, and their effectiveness depends on clear reasoning, accuracy, and helpful explanations.
In mathematics-related use cases, AI systems must demonstrate rigorous formal reasoning, conceptual clarity, and mathematical correctness. 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 AI model behavior in mathematical contexts
- Evaluate large language model (LLM) responses to mathematics-related queries for correctness, rigor, and logical coherence
- Verify mathematical claims, derivations, and proofs using deep domain expertise
- Conduct fact-checking using authoritative public sources and mathematical knowledge
- Annotate model responses by identifying strengths, weaknesses, and factual or conceptual errors
- Assess clarity, structure, and suitability of explanations for different audience levels
- Ensure outputs align with expected conversational standards and evaluation guidelines
- Apply consistent evaluation frameworks, benchmarks, and taxonomies across tasks
Who You Are
- PhD in Mathematics or a closely related field
- Demonstrated expertise in Probability & Statistics, with experience in one or more of the following areas:
- Algebra & Number Theory
- Calculus & Analysis
- Geometry & Topology
- Discrete Mathematics, Logic & Computation
- Comfortable working with large language models and understanding real-world usage patterns
- Excellent written communication skills with the ability to explain complex concepts clearly
- Strong attention to detail and ability to identify subtle logical or conceptual issues
- Experience reviewing, editing, or evaluating technical or academic writing
Nice-to-Have Specialties
- Prior experience with RLHF, model evaluation, or data annotation
- Teaching, mentoring, or explaining mathematics to non-expert audiences
- Familiarity with structured evaluation rubrics, benchmarks, or review frameworks
What Success Looks Like
- You consistently identify inaccuracies or weak reasoning in mathematical AI outputs
- Your feedback improves rigor, correctness, and clarity of model responses
- You deliver reliable, reproducible evaluation artifacts that strengthen AI performance
- The client’s AI systems are trusted in mathematical contexts due to your rigorous evaluations
Why Join This Project
This opportunity allows mathematicians to apply deep theoretical expertise to the evaluation and improvement of cutting-edge AI systems. The role is fully remote and flexible, enabling you to directly influence how mathematical reasoning is represented and communicated at scale.
Contract and Payment Terms
- Engagement as an independent contractor
- Fully remote with flexible scheduling
- Projects may be extended, shortened, or concluded based on performance and project needs
- Work will not involve access to confidential or proprietary information from any employer, client, or institution
- Payments are issued weekly via Stripe or Wise based on services rendered
- H1-B and STEM OPT candidates cannot be supported at this time
Key skills/competency
- Mathematical Reasoning
- Large Language Models (LLM)
- AI Model Evaluation
- Prompt Engineering
- Probability & Statistics
- Algebra & Number Theory
- Calculus & Analysis
- Discrete Mathematics
- Logical Coherence
- Technical Communication
How to Get Hired at Keystone Recruitment
- Tailor your resume for Keystone Recruitment: Highlight your PhD, specialized mathematical expertise, and any experience interacting with AI or large language models to show direct relevance to the Math Expert role.
- Showcase deep domain knowledge: Prepare to discuss your expertise in Probability & Statistics, Algebra, Calculus, Geometry, and Discrete Mathematics, providing specific examples of complex problem-solving.
- Demonstrate exceptional communication skills: Be ready to articulate how you've simplified complex mathematical concepts for diverse audiences, crucial for explaining AI model feedback.
- Prepare for technical evaluations: Practice verifying mathematical claims, derivations, and proofs, reflecting the core responsibilities of a Math Expert.
- Familiarize yourself with AI evaluation principles: Research best practices in LLM evaluation, data annotation, and structured rubrics to align with the project's focus on improving AI systems.
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