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Mathematics Expert

Turing · Remote

Pay
See listing
Where
Worldwide
Degree
See listing
Posted
5d ago
Checked
today
Before you applyHow to pass the Turing assessment and interviewsMost people who don't get in fail the screening, not the CV. Five minutes here first.

What the work is

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.

Who gets hired

  • 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.

Education & Experience

  • 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.

Offer Details

  • 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

Evaluation Process -

  • Shortlisted candidates will be sent a Job Interest Form.
  • Final selected candidates will be contacted with the next steps, including onboarding requirements.

Pay

See listing, fully remote. How payouts and tax work.

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