A leading US-based company seeks detail-oriented individuals with strong mathematical and analytical skills to create, evaluate, and refine prompts and responses in mathematical reasoning, logic puzzles, and critical thinking. This role involves assessing AI-generated outputs for accuracy, clarity, and logical soundness to enhance the performance of advanced AI models. A deep understanding of mathematical concepts is essential to produce high-quality annotations that support model training and evaluation.Key Responsibilities:Solve competitive math problems involving reasoning, logic, and critical thinking.Evaluate AI outputs for correctness, clarity, and logical consistency.Annotate responses using detailed feedback and predefined rubrics.Identify and flag low-quality or ambiguous content.Collaborate with leads and reviewers to ensure annotation consistency.Meet performance targets for volume, quality, and handling time.Contribute to evolving guidelines based on edge cases and task trends.Participate in calibration sessions to align on annotation standards.Help document best practices and workflow improvements.Required Qualifications:4+ years of experience in mathematics-related roles.Academic or professional background in Mathematics, Physics, Computer Science, or related fields.Research or teaching experience in Mathematics.Excellent English communication skills, especially for expressing mathematical ideas.Strong problem-solving skills in university-level or competition-level math.Ability to create logic puzzles and analytical challenges.Proficiency in at least three key domains: algebra, calculus, probability, discrete math, number theory, logic, algorithms, or game theory.Preferred Qualifications:Ph.D. in Mathematics, Physics, or Statistics.Experience developing educational content, puzzles, or logic materials.Familiarity with AI and LLM concepts.Experience in data annotation, especially in mathematical contexts.Note: Shortlisted candidates may be asked to complete an assessment.
Job Title
Remote Mathematics LLM Trainer - 30114