Aryav S.

Key Skills

Software

Mercor

Don't disclose

Top Subject Matter

LLM training dataset labeling and evaluation

AI tutoring / programming education and grading support

Top Data Types

Text

Top Task Types

Fine-tuning

Freelancer Overview

LLM Eval (Dataset labeling and validation for supervised fine-tuning). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Mercor and Don't disclose. Education includes Bachelor of Science, Texas A&M University (2027). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Fine-tuning, Evaluation, and Rating.

Labeling Experience

Peer Teacher/Teaching Assistant, ENGR 102

Don't disclose

Supported 150+ first-year engineering students by helping them learn and apply Python programming concepts through targeted guidance. Led 10+ weekly office hours and review sessions, assisting students in debugging assignments and preparing for exams. Assisted in grading 200+ coding assignments and exams while providing structured feedback on correctness, readability, edge cases, and Python best practices. • Reviewed student code submissions and evaluated correctness • Provided instructional feedback to improve programming solutions • Conducted debugging support during office hours • Graded assignments and exams with quality-focused criteria

2025 - Present

LLM Eval (Dataset labeling and validation for supervised fine-tuning)

MercorTextFine-tuning

Labeled and submitted 500+ high-quality problem-solution pairs into LLM training datasets to improve supervised fine-tuning data quality. Flagged 200+ inaccurate model outputs during validation to increase dataset consistency by 20% and reduce low-quality examples. Identified 30+ prompt edge cases and formatting issues to speed up evaluation and QA workflow quality improvements by 25%. • Worked on LLM dataset preparation and validation review cycles • Performed error/quality flagging on model outputs • Audited prompts for edge cases and formatting defects • Contributed to dataset consistency improvements for training readiness

2025 - 2025

Education

Work History