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LLM Trainer: Reasoning Specialist

Turing

Verified listing
Full-time
RemotePosted YesterdayNot disclosed

Overview

This role involves creating, evaluating, and refining prompts and responses for mathematical reasoning and logic problems to train advanced AI models. You will assess AI-generated outputs for accuracy and clarity, annotate them with detailed feedback, and help ensure the reliability and robustness of model performance through high-quality training data.

What You’ll Do

  • Solve a wide variety of competitive mathematical problems covering mathematical reasoning, logic, and critical thinking topics
  • Evaluate AI-generated responses for correctness, clarity, logical coherence, and depth of mathematical understanding
  • Annotate model outputs with detailed feedback and labels based on predefined quality guidelines and rubric standards
  • Identify and flag ambiguous, incorrect, or low-quality data to support continuous model improvement
  • Collaborate with leads and reviewers to maintain consistency and accuracy in annotations
  • Maintain performance metrics such as task completion volume, quality scores, and adherence to Average Handling Time (AHT) guidelines
  • Provide input on evolving annotation guidelines based on real-time task patterns and edge cases
  • Participate in calibration sessions to align on annotation standards and reduce quality variations across annotators
  • Support the documentation of best practices, tooling issues, and annotation workflows for team-wide knowledge sharing

Requirements

  • Academic or professional background in Mathematics, Physics, Computer Science, or related quantitative fields
  • Research experience in Mathematics or teaching experience in the subject
  • Exceptional English communication skills, particularly in expressing mathematical and logical ideas clearly and precisely
  • Strong foundational knowledge in mathematics, logic, and problem-solving techniques
  • Ability to create compelling logic puzzles, mathematical scenarios, and analytical challenges
  • Excellent analytical and logical reasoning abilities in solving university-level or competition-level math problems and logic puzzles
  • Strong understanding of at least three key mathematical domains, including but not limited to algebra, calculus, probability, discrete mathematics, number theory, mathematical logic, algorithms, and game theory

Who Should Apply

This role suits mathematicians, physicists, or competitive programmers who are rigorous, detail-oriented, and enjoy solving hard problems—especially those with research or teaching experience who can articulate why a solution is correct or why an AI response misses the mark. It will frustrate someone who views math as just a means to an end, or who doesn't want to spend time writing detailed explanations and calibrating standards with a team.

Salary Insight

No salary information was provided in the posting. Before investing time in an application, research comparable AI data annotation and training roles—these typically range from contract to full-time and vary widely by region and company. Ask about compensation structure early (hourly, per-task, or salary), whether it's contract or employment, and what the expected volume and time commitment are.

Required Skills

Mathematical reasoningLogic puzzlesLLM trainingData annotationProblem solving

Compensation

Not disclosed

Location
Remote
Engagement
Full-time
Posted
Yesterday

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About Turing

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Remote policy: Remote worldwide, but location eligibility varies by individual project. Many AI roles require minimum hours per week and U.S. Pacific Time overlap. Contractors and freelancers only, not employees.

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Application Tip

Lead with a specific mathematical problem you've solved or taught—ideally one that required you to explain not just the answer but the reasoning and common misconceptions. This role is fundamentally about quality annotation and communication of mathematical thinking, so a portfolio example or detailed case study of how you'd evaluate and improve an AI-generated solution will stand out far more than a list of domains you know. Mention any experience with rubric-based evaluation or training others, as calibration and consistency are core to the work.

Sourced from MyRemoteJobs · verified against the original posting