Remote Mathematics Researcher; PhD

Role Overview

Remote contract for PhDs in Mathematics, Statistics, or related fields. Work on cutting-edge projects with top AI labs while earning upto $150/hr, fully remote, with flexible weekly hours.

We seek mathematics researchers with advanced analytical skills to design, test, and refine math problem sets for evaluating and improving large language models (LLMs). Your work directly enhances how AI solves multi-step reasoning and logic problems.

• Create advanced math challenges (e.g., combinatorics, linear algebra, logic reasoning)
• Evaluate AI-generated solutions for accuracy and reasoning quality
• Refine benchmarks in collaboration with global math researchers
• Prepare reports and publish results in academic venues

• PhD (pursuing or completed) in Mathematics, Applied Mathematics, Statistics, or related
• Strong mathematical reasoning and problem-solving skills
• Experience in academic research and technical writing
• Clear, concise communication—able to give structured feedback

• Compensation: $50–$150 per hour, based on skills and experience. (paid once every two weeks).
• Duration: 1 week to 3 months (project-based; extension possible).
• Hours:
  
  Up to 30 hrs/week.
• Time Zone: 2–5 hrs/day overlap with UTC-8 (America/), confirmed near onboarding.

The evaluation and onboarding process takes just 80–90 mins

• Collaboration:
  
  Work alongside global experts and leading AI labs.
• Remote:
  Remote-first role with weekly hour options tailored to your schedule.
• Career Growth:
  Gain exposure to cutting-edge AI research and future-proof your career at the intersection of physics and artificial intelligence.
• Opportunity:
  High-performing contributors may receive contract extensions and invitations to additional AI research projects.

Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems.

Turing helps customers in two ways:
Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM, and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.