Remote Maths AI Trainer (PhD) - 34430

Turing

Bengaluru

Remote

INR 1,102,000 - 2,480,000

Part time

14 days+

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Job summary

A leading AI company is seeking researchers to assist in evaluating large language models. Candidates must hold a PhD in Mathematics or a related field. Responsibilities include solving complex mathematical tasks and contributing to research independence in a remote environment. This is a contract position requiring a minimum commitment of 20 hours per week with flexible hour options. Ideal for those interested in cutting-edge AI work.

Qualifications

  • Candidates must have a solid foundation in advanced mathematics.
  • Strong problem-solving skills are essential.
  • Ability to communicate complex topics clearly.

Responsibilities

  • Assist in fine-tuning and evaluating large language models.
  • Complete tasks related to advanced mathematical problems.
  • Collaborate in a remote research environment.

Skills

Strong mathematical and analytical skills
Communication clarity
Independent research capability
Research independence
Communication skills

Education

PhD/Postdoc in Mathematics, Applied Mathematics, or Statistics

Job description

Overview

We are seeking researchers with strong mathematical and analytical backgrounds to assist in fine-tuning and evaluating large language models (LLMs). Your work will help LLMs improve their ability to understand and solve complex math problems, such as multi-step algebra or logic questions.

Research Objectives

As a contributor to this research-focused initiative, you may be asked to complete tasks such as:

  • Determine the number of real 5×55 × 55×5 symmetric matrices of rank 2 whose entries are only 0 or 1.
  • How many subsets of a 10-element set exist such that the characteristic vector of each subset has Hamming weight exactly 3?
  • How many distinct 10-digit numbers exist where the sum of the digits is divisible by 3, and each digit is either 0 or 1?

These tasks are designed to find model weaknesses and improve training and evaluation workflows.

Candidate Profile
  • Academic Background: Enrolled in or completed a PhD/Postdoc in Mathematics, Applied Mathematics, Statistics, or a related field.
  • Analytical Skills: Strong ability to solve advanced math problems with clear and structured reasoning.
  • Communication Skills: Clarity in explaining complex topics and providing feedback with precision.
  • Research Independence: Ability to work independently in a remote research environment and participate actively in team discussions.
  • Technical Setup: Access to a reliable computer and internet setup to participate in remote assignments.

Note: This position is open only to candidates who have completed or are currently pursuing a Ph.D.; applications that do not meet this criterion will not be considered.

Time Commitment & Contract Details
  • Commitments Required: at least 4 hours per day and minimum 20 hours per week with 4 hours of overlap with PST. (Options: 20 hrs/week, 30 hrs/week, or 40 hrs/week)
  • Engagement type: Contractor assignment/freelancer (no medical/paid leave)
  • Duration of contract: 1 month; start date expected next week
  • Selection Process: Task-based assessment for shortlisted candidates, followed by a contract offer with defined timelines and workload.
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.

Why work with Turing?
  • Work on research that directly impacts the future of language model performance in mathematics and STEM.
  • Collaborate with a global network of experts shaping next-generation AI benchmarks.
  • Gain exposure to cutting-edge model evaluation strategies in an academic–industry hybrid setting.
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