Researcher – Mathematics

Company Description

Dusker AI specializes in evaluating and benchmarking advanced AI systems through rigorous, research-driven methodologies. We partner with organizations developing large language models, AI agents, and autonomous systems to measure performance across reasoning, reliability, adaptability, safety, and domain expertise.

Our evaluation frameworks are designed by subject matter experts and researchers, enabling deeper assessment than traditional benchmarks. By identifying strengths, uncovering failure modes, and testing real-world capabilities, Dusker AI helps organizations build AI systems that are robust, trustworthy, and deployment-ready.

We work across a wide range of domains including mathematics, physics, chemistry, biology, software engineering, and applied sciences, creating high-quality evaluation datasets and benchmark suites that drive the next generation of AI performance.

Role Description

Researcher – Mathematics

Compensation: $20–$25 per accepted task

Location: Remote

Education Requirement: Master's or PhD

Publication Requirement: Peer-reviewed publications, conference papers, journal articles, preprints, or equivalent research contributions preferred.

Application Requirements

Applicants are strongly encouraged to include links to their Google Scholar profile, ResearchGate profile, ORCID profile, published papers, personal academic website, or other verifiable research publications within their CV/Resume.

Applications with demonstrated research experience and accessible publication records will be prioritized during the review process.

We are seeking a highly analytical Mathematics Researcher to contribute to the design and evaluation of advanced AI systems. This remote position focuses on developing mathematically rigorous benchmarks, evaluating quantitative reasoning capabilities, and conducting research at the intersection of mathematics and artificial intelligence.

The successful candidate will formulate challenging mathematics-based tasks, analyze mathematical reasoning, assess model behavior, and develop evaluation methodologies that measure the accuracy, consistency, robustness, and problem-solving capabilities of advanced AI systems.

Key Responsibilities

• Design rigorous mathematics benchmark tasks and evaluation frameworks for AI systems

• Develop challenging mathematics problems covering algebra, calculus, linear algebra, geometry, trigonometry, number theory, probability, statistics, discrete mathematics, optimization, and related disciplines

• Create scientifically accurate evaluation criteria and assessment methodologies

• Analyze AI-generated responses and identify strengths, weaknesses, reasoning errors, logical inconsistencies, and failure patterns

• Conduct literature-based research to support benchmark development and mathematical validation

• Evaluate model performance on mathematical reasoning, proof construction, quantitative analysis, and problem-solving tasks

• Collaborate with multidisciplinary teams to improve benchmark quality, coverage, and evaluation methodologies

• Document methodologies, findings, and evaluation results through technical reports and research summaries

• Contribute to benchmark datasets, evaluation frameworks, and internal research initiatives

• Stay informed about developments in mathematics, AI evaluation, reasoning assessment, and AI safety

Role Qualifications

Required

• Master's or PhD in Mathematics, Applied Mathematics, Statistics, Operations Research, Mathematical Sciences, Pure Mathematics, Computational Mathematics, or a closely related discipline

• Demonstrated research experience with peer-reviewed publications, conference papers, journal articles, or equivalent scholarly contributions

• Strong foundation in algebra, calculus, linear algebra, geometry, probability, statistics, discrete mathematics, and mathematical reasoning

• Experience with mathematical proof techniques, quantitative analysis, and advanced problem-solving

• Experience with academic research, literature review, and evidence-based analysis

• Strong analytical and critical thinking skills

• Excellent written and verbal communication skills in English

• Ability to work independently in a remote research environment

Preferred

• PhD degree in Mathematics, Applied Mathematics, Statistics, Operations Research, or a specialized mathematical discipline

• Multiple peer-reviewed publications in recognized journals or conferences

• Experience evaluating AI systems, machine learning models, or large language models

• Expertise in one or more specialized areas such as algebra, analysis, topology, number theory, probability theory, statistics, combinatorics, optimization, mathematical logic, graph theory, or applied mathematics

• Experience developing benchmarks, datasets, mathematical assessments, competitions, or evaluation frameworks

• Familiarity with AI safety, model alignment, AI benchmarking methodologies, or reasoning evaluation

• Experience reviewing mathematical manuscripts, academic assessments, grant proposals, or research publications

Candidates with strong academic research backgrounds, publication records, demonstrated expertise in mathematical sciences, and exceptional quantitative reasoning skills are especially encouraged to apply.