COMPUTATIONAL MATHEMATICIAN - FULLY REMOTE | UPTO $70/HR

About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey . Position: Mathematics PhD Coding Experts Type: Contract Compensation: $70/hour Location: Remote Duration: 6 weeks Commitment: 20+ hours/week Role Responsibilities • Source material from published papers, Kaggle datasets , open-source repositories, or self-designed scenarios. • Write scientific prompts based on sourced inputs. • Build grading criteria to define correct answers. • Calibrate tasks against frontier models, ensuring tasks ship only when strong models fail more often than succeed. • Work independently and asynchronously to meet deadlines while improving AI model performance . Qualifications Must-Have • PhD in mathematics, applied mathematics, computational mathematics, or a closely related field. • Depth in at least two subdomains: numerical linear algebra, computational mechanics, computational finance. • Working proficiency in Python for scientific computing. • Comfortable with Git/GitHub and running code in Docker . Preferred • Publications in peer-reviewed journals. • Prior scientific software or research engineering experience. Start Date • Immediate Interview Process • Upload your resume and application form. • A 25-minute conversational interview covering your background, experience, and motivations. • Follow up within a few days with next steps and onboarding. Application Process (Takes 20–30 mins to complete) • Upload resume • AI interview based on your resume • Submit form Resources & Support • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome • For any help or support, reach out to: support@mercor.com PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.