Mathematics PhD Coding Experts

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Mathematics PhD Coding Expert based in Canada.

This is a specialized opportunity for a mathematics researcher with strong scientific computing and coding expertise to help shape the next generation of AI <systems.You> will create original, executable research problems designed to challenge advanced frontier models.Your work will combine deep mathematical knowledge with practical programming and rigorous <evaluation.You>’ll develop scientific prompts, define grading criteria, and assess whether AI-generated solutions meet demanding standards.The role offers the opportunity to apply your research expertise beyond traditional academic settings while contributing to cutting-edge AI <evaluation.You>’ll work remotely and independently, with a flexible schedule and a focused, research-driven engagement.This is an ideal opportunity for a mathematically rigorous professional who enjoys translating complex scientific concepts into challenging computational problems.

Accountabilities

• Source relevant scientific material from published research, Kaggle datasets, open-source repositories, or original scenarios to develop challenging computational problems.
• Design original scientific prompts that require meaningful mathematical reasoning and executable solutions.
• Create clear, rigorous grading criteria that define what constitutes a correct and high-quality solution.
• Develop tasks with a strong coding focus across relevant mathematical domains such as numerical linear algebra, computational mechanics, and computational finance.
• Execute and validate submitted code to ensure that tasks are technically sound, reproducible, and appropriately challenging.
• Calibrate tasks against advanced AI models, refining them until they reliably distinguish between strong and unsuccessful model performance.
• Apply deep subject-matter expertise to ensure that evaluation tasks accurately reflect real scientific and computational challenges.
• Collaborate through a structured Git/GitHub and pull-request workflow, following automated quality checks and technical standards.

Requirements

• PhD in Mathematics, Applied Mathematics, Computational Mathematics, or a closely related discipline.
• Demonstrated depth and expertise in at least two of the following areas: numerical linear algebra, computational mechanics, and computational finance.
• Working proficiency in Python or R for scientific computing and computational problem-solving.
• Strong understanding of mathematical modeling, numerical methods, and scientific computation.
• Comfortable working with Git/GitHub, including pull requests and version-controlled workflows.
• Experience running and validating code in Docker or similar containerized environments.
• Ability to translate complex mathematical and scientific concepts into precise, executable programming challenges.
• Strong analytical and problem-solving skills, with exceptional attention to technical accuracy and rigor.
• Ability to work independently, manage priorities, and deliver high-quality research tasks within defined timelines.
• Preferred: Peer-reviewed publications demonstrating research depth in relevant mathematical or computational fields.
• Preferred: Previous experience in scientific software development, research engineering, or computational research.

Benefits

• Fully remote: Work from anywhere in Canada and complete the engagement on your own schedule.
• Flexible part-time commitment: Approximately 20+ hours per week.
• 6-week engagement: Immediate start with the possibility of projects being extended, shortened, or concluded early depending on project needs and performance.
• Independent contractor arrangement: Work as a contractor with flexibility and autonomy.
• Weekly payments: Compensation paid weekly through Stripe or Wise based on services delivered.
• AI and research impact: Apply your mathematical expertise to projects focused on evaluating and improving advanced AI systems.
• Research-driven work: Collaborate on challenging scientific computing tasks designed to push the capabilities of frontier AI models.
• Referral opportunity: Eligible participants can earn up to $280 per successful referral, subject to applicable restrictions.
• Privacy and confidentiality: Projects are designed without requiring access to confidential or proprietary information from previous employers, clients, or institutions.
• Important eligibility note: H-1B and STEM OPT candidates are not currently supported for this engagement.