Mathematics Expert

About Turing
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.

Role Overview
In this role, you will work on cutting-edge initiatives to fine-tune large language models by leveraging your deep analytical skills and mathematics expertise. The ideal candidate possesses a strong foundation in Mathematics —spanning advanced engineering entrance levels through graduate and PhD-level concepts—and the ability to break down complex phenomena into clear, step-by-step reasoning. You will play a direct role in probing model limitations while learning how to leverage frontier AI tools to future-proof your career.

Requirements

• Core Skills: Strong analytical, research, and problem-solving skills with excellent English comprehension.

• Communication & Feedback: Exceptional structured written communication, with the ability to provide constructive feedback and detailed annotations in a remote environment.

• Analytical & Creative Thinking: Strong lateral thinking capabilities to construct novel scenarios and evaluate complex reasoning pathways.

• Independence: Self-motivated and capable of operating independently in a fast-paced, remote-first setup.

• Technical Infrastructure: Personal desktop/laptop equipped with a stable, high-speed internet connection.

Responsibilities
In this role, you will help set the benchmark for AI capabilities in advanced physical sciences. Your day-to-day responsibilities will include:

• Problem Creation & Solutioning: Designing and solving challenging physics problems that test the boundaries of large language models.

• Authoring Gold-Standard Data: Creating clear, high-quality, step-by-step solutions with detailed and articulated reasoning.

• Research Collaboration: Working with LLM researchers to align task designs with evaluation goals, targeting key areas where models struggle (e.g., symbolic manipulation, abstraction, multi-step reasoning).

- Benchmark Definition: Helping define and build new evaluation benchmarks across physics curricula ranging from early undergraduate to PhD-level topics.

• Benchmark Definition: Helping define and build new evaluation benchmarks across physics curricula ranging from early undergraduate to PhD-level topics.

• Educational background or Doctorate in Mathematics, or an equivalent technical field.

- Experience in AI evaluation, data annotation, content review, quality assurance, or a related analytical role is preferred but not required.

• Experience in AI evaluation, data annotation, content review, quality assurance, or a related analytical role is preferred but not required.

• Commitments Required: at least 4 hours per day and upto 40 hours per week with 4 hours of overlap with PST.

• Engagement type: Contractor

- Engagement Length: 12 weeks

• Engagement Length: 12 weeks

• Shortlisted candidates will be sent a Job Interest Form .

• Final selected candidates will be contacted with the next steps, including onboarding requirements.